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a/translations/id/1-Introduction/1-intro-to-ML/README.md +++ b/translations/id/1-Introduction/1-intro-to-ML/README.md @@ -1,12 +1,3 @@ - # Pengantar Pembelajaran Mesin ## [Kuis Pra-Pelajaran](https://ff-quizzes.netlify.app/en/ml/) diff --git a/translations/id/1-Introduction/1-intro-to-ML/assignment.md b/translations/id/1-Introduction/1-intro-to-ML/assignment.md index 37614684a..1e34f32b4 100644 --- a/translations/id/1-Introduction/1-intro-to-ML/assignment.md +++ b/translations/id/1-Introduction/1-intro-to-ML/assignment.md @@ -1,12 +1,3 @@ - # Memulai dan Berjalan ## Instruksi diff --git a/translations/id/1-Introduction/2-history-of-ML/README.md b/translations/id/1-Introduction/2-history-of-ML/README.md index b288fb439..e548d635b 100644 --- a/translations/id/1-Introduction/2-history-of-ML/README.md +++ b/translations/id/1-Introduction/2-history-of-ML/README.md @@ -1,12 +1,3 @@ - # Sejarah Pembelajaran Mesin ![Ringkasan Sejarah Pembelajaran Mesin dalam bentuk sketchnote](../../../../sketchnotes/ml-history.png) diff --git a/translations/id/1-Introduction/2-history-of-ML/assignment.md b/translations/id/1-Introduction/2-history-of-ML/assignment.md index 98bcc9e5d..6e562af6c 100644 --- a/translations/id/1-Introduction/2-history-of-ML/assignment.md +++ b/translations/id/1-Introduction/2-history-of-ML/assignment.md @@ -1,12 +1,3 @@ - # Buat sebuah garis waktu ## Instruksi diff --git a/translations/id/1-Introduction/3-fairness/README.md b/translations/id/1-Introduction/3-fairness/README.md index 1db4108b4..612225449 100644 --- a/translations/id/1-Introduction/3-fairness/README.md +++ b/translations/id/1-Introduction/3-fairness/README.md @@ -1,12 +1,3 @@ - # Membangun Solusi Machine Learning dengan AI yang Bertanggung Jawab ![Ringkasan AI yang bertanggung jawab dalam Machine Learning dalam bentuk sketchnote](../../../../sketchnotes/ml-fairness.png) diff --git a/translations/id/1-Introduction/3-fairness/assignment.md b/translations/id/1-Introduction/3-fairness/assignment.md index afb21da4d..88566811e 100644 --- a/translations/id/1-Introduction/3-fairness/assignment.md +++ b/translations/id/1-Introduction/3-fairness/assignment.md @@ -1,12 +1,3 @@ - # Jelajahi Responsible AI Toolbox ## Instruksi diff --git a/translations/id/1-Introduction/4-techniques-of-ML/README.md b/translations/id/1-Introduction/4-techniques-of-ML/README.md index 32917d448..3501c8705 100644 --- a/translations/id/1-Introduction/4-techniques-of-ML/README.md +++ b/translations/id/1-Introduction/4-techniques-of-ML/README.md @@ -1,12 +1,3 @@ - # Teknik Pembelajaran Mesin Proses membangun, menggunakan, dan memelihara model pembelajaran mesin serta data yang digunakan sangat berbeda dari banyak alur kerja pengembangan lainnya. Dalam pelajaran ini, kita akan mengungkap proses tersebut dan merangkum teknik utama yang perlu Anda ketahui. Anda akan: diff --git a/translations/id/1-Introduction/4-techniques-of-ML/assignment.md b/translations/id/1-Introduction/4-techniques-of-ML/assignment.md index d06517e4a..043b682f1 100644 --- a/translations/id/1-Introduction/4-techniques-of-ML/assignment.md +++ b/translations/id/1-Introduction/4-techniques-of-ML/assignment.md @@ -1,12 +1,3 @@ - # Wawancara dengan seorang data scientist ## Instruksi diff --git a/translations/id/1-Introduction/README.md b/translations/id/1-Introduction/README.md index adba51d2e..ce15ebab7 100644 --- a/translations/id/1-Introduction/README.md +++ b/translations/id/1-Introduction/README.md @@ -1,12 +1,3 @@ - # Pengantar pembelajaran mesin Di bagian kurikulum ini, Anda akan diperkenalkan pada konsep dasar yang mendasari bidang pembelajaran mesin, apa itu, serta mempelajari sejarahnya dan teknik yang digunakan para peneliti untuk bekerja dengannya. Mari kita jelajahi dunia baru ML ini bersama-sama! diff --git a/translations/id/2-Regression/1-Tools/README.md b/translations/id/2-Regression/1-Tools/README.md index 377d00fc1..d34db8f5d 100644 --- a/translations/id/2-Regression/1-Tools/README.md +++ b/translations/id/2-Regression/1-Tools/README.md @@ -1,12 +1,3 @@ - # Memulai dengan Python dan Scikit-learn untuk model regresi ![Ringkasan regresi dalam sketchnote](../../../../sketchnotes/ml-regression.png) diff --git a/translations/id/2-Regression/1-Tools/assignment.md b/translations/id/2-Regression/1-Tools/assignment.md index b3544176a..946aebeb8 100644 --- a/translations/id/2-Regression/1-Tools/assignment.md +++ b/translations/id/2-Regression/1-Tools/assignment.md @@ -1,12 +1,3 @@ - # Regresi dengan Scikit-learn ## Instruksi diff --git a/translations/id/2-Regression/1-Tools/solution/Julia/README.md b/translations/id/2-Regression/1-Tools/solution/Julia/README.md index 16d0bfea6..9a9cced84 100644 --- a/translations/id/2-Regression/1-Tools/solution/Julia/README.md +++ b/translations/id/2-Regression/1-Tools/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/id/2-Regression/2-Data/README.md b/translations/id/2-Regression/2-Data/README.md index ee58546dd..eb5f027a1 100644 --- a/translations/id/2-Regression/2-Data/README.md +++ b/translations/id/2-Regression/2-Data/README.md @@ -1,12 +1,3 @@ - # Membangun Model Regresi Menggunakan Scikit-learn: Persiapkan dan Visualisasikan Data ![Infografis visualisasi data](../../../../2-Regression/2-Data/images/data-visualization.png) diff --git a/translations/id/2-Regression/2-Data/assignment.md b/translations/id/2-Regression/2-Data/assignment.md index ff72db44c..c60aeba82 100644 --- a/translations/id/2-Regression/2-Data/assignment.md +++ b/translations/id/2-Regression/2-Data/assignment.md @@ -1,12 +1,3 @@ - # Menjelajahi Visualisasi Ada beberapa pustaka berbeda yang tersedia untuk visualisasi data. Buat beberapa visualisasi menggunakan data Pumpkin dalam pelajaran ini dengan matplotlib dan seaborn di notebook contoh. Pustaka mana yang lebih mudah digunakan? diff --git a/translations/id/2-Regression/2-Data/solution/Julia/README.md b/translations/id/2-Regression/2-Data/solution/Julia/README.md index d4cfec252..9a9cced84 100644 --- a/translations/id/2-Regression/2-Data/solution/Julia/README.md +++ b/translations/id/2-Regression/2-Data/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/id/2-Regression/3-Linear/README.md b/translations/id/2-Regression/3-Linear/README.md index 08af37410..9cea8abdb 100644 --- a/translations/id/2-Regression/3-Linear/README.md +++ b/translations/id/2-Regression/3-Linear/README.md @@ -1,12 +1,3 @@ - # Membangun Model Regresi Menggunakan Scikit-learn: Empat Cara Regresi ![Infografik regresi linear vs polinomial](../../../../2-Regression/3-Linear/images/linear-polynomial.png) @@ -114,11 +105,11 @@ Sekarang setelah Anda memahami matematika di balik regresi linear, mari kita bua Dari pelajaran sebelumnya, Anda mungkin telah melihat bahwa harga rata-rata untuk berbagai bulan terlihat seperti ini: -Harga rata-rata berdasarkan bulan +Harga rata-rata berdasarkan bulan Ini menunjukkan bahwa seharusnya ada beberapa korelasi, dan kita dapat mencoba melatih model regresi linear untuk memprediksi hubungan antara `Bulan` dan `Harga`, atau antara `HariDalamTahun` dan `Harga`. Berikut adalah plot sebar yang menunjukkan hubungan yang terakhir: -Plot sebar Harga vs. Hari dalam Tahun +Plot sebar Harga vs. Hari dalam Tahun Mari kita lihat apakah ada korelasi menggunakan fungsi `corr`: @@ -137,7 +128,7 @@ for i,var in enumerate(new_pumpkins['Variety'].unique()): ax = df.plot.scatter('DayOfYear','Price',ax=ax,c=colors[i],label=var) ``` -Plot sebar Harga vs. Hari dalam Tahun +Plot sebar Harga vs. Hari dalam Tahun Penyelidikan kami menunjukkan bahwa jenis labu memiliki pengaruh lebih besar pada harga keseluruhan daripada tanggal penjualan sebenarnya. Kita dapat melihat ini dengan grafik batang: @@ -145,7 +136,7 @@ Penyelidikan kami menunjukkan bahwa jenis labu memiliki pengaruh lebih besar pad new_pumpkins.groupby('Variety')['Price'].mean().plot(kind='bar') ``` -Grafik batang harga vs jenis labu +Grafik batang harga vs jenis labu Mari kita fokus untuk sementara hanya pada satu jenis labu, yaitu 'pie type', dan lihat apa pengaruh tanggal terhadap harga: @@ -153,7 +144,7 @@ Mari kita fokus untuk sementara hanya pada satu jenis labu, yaitu 'pie type', da pie_pumpkins = new_pumpkins[new_pumpkins['Variety']=='PIE TYPE'] pie_pumpkins.plot.scatter('DayOfYear','Price') ``` -Plot sebar Harga vs. Hari dalam Tahun +Plot sebar Harga vs. Hari dalam Tahun Jika kita sekarang menghitung korelasi antara `Harga` dan `HariDalamTahun` menggunakan fungsi `corr`, kita akan mendapatkan sesuatu seperti `-0.27` - yang berarti bahwa melatih model prediktif masuk akal. @@ -228,7 +219,7 @@ plt.plot(X_test,pred) ``` -Regresi linear +Regresi linear ## Regresi Polinomial @@ -257,7 +248,7 @@ Menggunakan `PolynomialFeatures(2)` berarti kita akan menyertakan semua polinomi Pipeline dapat digunakan dengan cara yang sama seperti objek `LinearRegression` asli, yaitu kita dapat `fit` pipeline, lalu menggunakan `predict` untuk mendapatkan hasil prediksi. Berikut adalah grafik yang menunjukkan data uji dan kurva aproksimasi: -Regresi polinomial +Regresi polinomial Dengan menggunakan Regresi Polinomial, kita dapat memperoleh MSE yang sedikit lebih rendah dan determinasi yang lebih tinggi, tetapi tidak signifikan. Kita perlu mempertimbangkan fitur lainnya! @@ -275,7 +266,7 @@ Dalam dunia ideal, kita ingin dapat memprediksi harga untuk berbagai jenis labu Di sini Anda dapat melihat bagaimana harga rata-rata bergantung pada variasi: -Harga rata-rata berdasarkan variasi +Harga rata-rata berdasarkan variasi Untuk mempertimbangkan variasi, pertama-tama kita perlu mengonversinya ke bentuk numerik, atau **encode**. Ada beberapa cara untuk melakukannya: diff --git a/translations/id/2-Regression/3-Linear/assignment.md b/translations/id/2-Regression/3-Linear/assignment.md index 811070fdb..f67514b89 100644 --- a/translations/id/2-Regression/3-Linear/assignment.md +++ b/translations/id/2-Regression/3-Linear/assignment.md @@ -1,12 +1,3 @@ - # Membuat Model Regresi ## Instruksi diff --git a/translations/id/2-Regression/3-Linear/solution/Julia/README.md b/translations/id/2-Regression/3-Linear/solution/Julia/README.md index eb1154c88..9a9cced84 100644 --- a/translations/id/2-Regression/3-Linear/solution/Julia/README.md +++ b/translations/id/2-Regression/3-Linear/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/id/2-Regression/4-Logistic/README.md b/translations/id/2-Regression/4-Logistic/README.md index 987b7f3fe..209b363ff 100644 --- a/translations/id/2-Regression/4-Logistic/README.md +++ b/translations/id/2-Regression/4-Logistic/README.md @@ -1,12 +1,3 @@ - # Regresi Logistik untuk Memprediksi Kategori ![Infografik regresi logistik vs regresi linear](../../../../2-Regression/4-Logistic/images/linear-vs-logistic.png) diff --git a/translations/id/2-Regression/4-Logistic/assignment.md b/translations/id/2-Regression/4-Logistic/assignment.md index 2f3e342db..88dc23cb2 100644 --- a/translations/id/2-Regression/4-Logistic/assignment.md +++ b/translations/id/2-Regression/4-Logistic/assignment.md @@ -1,12 +1,3 @@ - # Mencoba Ulang Beberapa Regresi ## Instruksi diff --git a/translations/id/2-Regression/4-Logistic/solution/Julia/README.md b/translations/id/2-Regression/4-Logistic/solution/Julia/README.md index 2cfbb092b..b4b57d49d 100644 --- a/translations/id/2-Regression/4-Logistic/solution/Julia/README.md +++ b/translations/id/2-Regression/4-Logistic/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/id/2-Regression/README.md b/translations/id/2-Regression/README.md index 7b7e5ebb9..f3b0c4ae1 100644 --- a/translations/id/2-Regression/README.md +++ b/translations/id/2-Regression/README.md @@ -1,12 +1,3 @@ - # Model regresi untuk pembelajaran mesin ## Topik regional: Model regresi untuk harga labu di Amerika Utara 🎃 diff --git a/translations/id/3-Web-App/1-Web-App/README.md b/translations/id/3-Web-App/1-Web-App/README.md index 860e4bce3..aea51fcc1 100644 --- a/translations/id/3-Web-App/1-Web-App/README.md +++ b/translations/id/3-Web-App/1-Web-App/README.md @@ -1,12 +1,3 @@ - # Membangun Aplikasi Web untuk Menggunakan Model ML Dalam pelajaran ini, Anda akan melatih model ML pada kumpulan data yang luar biasa: _Penampakan UFO selama abad terakhir_, yang bersumber dari database NUFORC. diff --git a/translations/id/3-Web-App/1-Web-App/assignment.md b/translations/id/3-Web-App/1-Web-App/assignment.md index 58aca7457..5b5ab32c7 100644 --- a/translations/id/3-Web-App/1-Web-App/assignment.md +++ b/translations/id/3-Web-App/1-Web-App/assignment.md @@ -1,12 +1,3 @@ - # Coba model yang berbeda ## Instruksi diff --git a/translations/id/3-Web-App/README.md b/translations/id/3-Web-App/README.md index 016a66e21..c5cef340f 100644 --- a/translations/id/3-Web-App/README.md +++ b/translations/id/3-Web-App/README.md @@ -1,12 +1,3 @@ - # Bangun Aplikasi Web untuk Menggunakan Model ML Anda Dalam bagian kurikulum ini, Anda akan diperkenalkan pada topik ML terapan: bagaimana cara menyimpan model Scikit-learn Anda sebagai file yang dapat digunakan untuk membuat prediksi dalam aplikasi web. Setelah model disimpan, Anda akan belajar cara menggunakannya dalam aplikasi web yang dibangun dengan Flask. Anda akan terlebih dahulu membuat model menggunakan beberapa data tentang penampakan UFO! Kemudian, Anda akan membangun aplikasi web yang memungkinkan Anda memasukkan jumlah detik bersama nilai lintang dan bujur untuk memprediksi negara mana yang melaporkan melihat UFO. diff --git a/translations/id/4-Classification/1-Introduction/README.md b/translations/id/4-Classification/1-Introduction/README.md index fbd799a25..589cdd3ac 100644 --- a/translations/id/4-Classification/1-Introduction/README.md +++ b/translations/id/4-Classification/1-Introduction/README.md @@ -1,12 +1,3 @@ - # Pengantar Klasifikasi Dalam empat pelajaran ini, Anda akan menjelajahi salah satu fokus utama dari pembelajaran mesin klasik - _klasifikasi_. Kita akan menggunakan berbagai algoritma klasifikasi dengan dataset tentang semua masakan luar biasa dari Asia dan India. Semoga Anda lapar! diff --git a/translations/id/4-Classification/1-Introduction/assignment.md b/translations/id/4-Classification/1-Introduction/assignment.md index f3d47b8e7..adc992c74 100644 --- a/translations/id/4-Classification/1-Introduction/assignment.md +++ b/translations/id/4-Classification/1-Introduction/assignment.md @@ -1,12 +1,3 @@ - # Jelajahi Metode Klasifikasi ## Instruksi diff --git a/translations/id/4-Classification/1-Introduction/solution/Julia/README.md b/translations/id/4-Classification/1-Introduction/solution/Julia/README.md index f741af189..9a9cced84 100644 --- a/translations/id/4-Classification/1-Introduction/solution/Julia/README.md +++ b/translations/id/4-Classification/1-Introduction/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/id/4-Classification/2-Classifiers-1/README.md b/translations/id/4-Classification/2-Classifiers-1/README.md index b899c4a2c..77486858a 100644 --- a/translations/id/4-Classification/2-Classifiers-1/README.md +++ b/translations/id/4-Classification/2-Classifiers-1/README.md @@ -1,12 +1,3 @@ - # Pengelompokan Masakan 1 Dalam pelajaran ini, Anda akan menggunakan dataset yang telah Anda simpan dari pelajaran sebelumnya, yang berisi data seimbang dan bersih tentang berbagai jenis masakan. diff --git a/translations/id/4-Classification/2-Classifiers-1/assignment.md b/translations/id/4-Classification/2-Classifiers-1/assignment.md index 96579cc65..74d0637fa 100644 --- a/translations/id/4-Classification/2-Classifiers-1/assignment.md +++ b/translations/id/4-Classification/2-Classifiers-1/assignment.md @@ -1,12 +1,3 @@ - # Pelajari Pemecah Masalah ## Instruksi diff --git a/translations/id/4-Classification/2-Classifiers-1/solution/Julia/README.md b/translations/id/4-Classification/2-Classifiers-1/solution/Julia/README.md index 213c0696d..186170c30 100644 --- a/translations/id/4-Classification/2-Classifiers-1/solution/Julia/README.md +++ b/translations/id/4-Classification/2-Classifiers-1/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/id/4-Classification/3-Classifiers-2/README.md b/translations/id/4-Classification/3-Classifiers-2/README.md index 917b4fc5c..73b72d091 100644 --- a/translations/id/4-Classification/3-Classifiers-2/README.md +++ b/translations/id/4-Classification/3-Classifiers-2/README.md @@ -1,12 +1,3 @@ - # Pengklasifikasi Masakan 2 Dalam pelajaran klasifikasi kedua ini, Anda akan mengeksplorasi lebih banyak cara untuk mengklasifikasikan data numerik. Anda juga akan mempelajari dampak dari memilih satu pengklasifikasi dibandingkan yang lain. diff --git a/translations/id/4-Classification/3-Classifiers-2/assignment.md b/translations/id/4-Classification/3-Classifiers-2/assignment.md index 676fc4c93..b1f82f09e 100644 --- a/translations/id/4-Classification/3-Classifiers-2/assignment.md +++ b/translations/id/4-Classification/3-Classifiers-2/assignment.md @@ -1,12 +1,3 @@ - # Parameter Play ## Instruksi diff --git a/translations/id/4-Classification/3-Classifiers-2/solution/Julia/README.md b/translations/id/4-Classification/3-Classifiers-2/solution/Julia/README.md index f3cee7cca..9a9cced84 100644 --- a/translations/id/4-Classification/3-Classifiers-2/solution/Julia/README.md +++ b/translations/id/4-Classification/3-Classifiers-2/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/id/4-Classification/4-Applied/README.md b/translations/id/4-Classification/4-Applied/README.md index 01c0be2bc..27e498718 100644 --- a/translations/id/4-Classification/4-Applied/README.md +++ b/translations/id/4-Classification/4-Applied/README.md @@ -1,12 +1,3 @@ - # Membangun Aplikasi Web Rekomendasi Masakan Dalam pelajaran ini, Anda akan membangun model klasifikasi menggunakan beberapa teknik yang telah Anda pelajari di pelajaran sebelumnya dan dengan dataset masakan lezat yang digunakan sepanjang seri ini. Selain itu, Anda akan membuat aplikasi web kecil untuk menggunakan model yang telah disimpan, memanfaatkan runtime web Onnx. diff --git a/translations/id/4-Classification/4-Applied/assignment.md b/translations/id/4-Classification/4-Applied/assignment.md index 9a884bb13..333e20383 100644 --- a/translations/id/4-Classification/4-Applied/assignment.md +++ b/translations/id/4-Classification/4-Applied/assignment.md @@ -1,12 +1,3 @@ - # Membangun Sistem Rekomendasi ## Instruksi diff --git a/translations/id/4-Classification/README.md b/translations/id/4-Classification/README.md index d20658481..14c9ac02d 100644 --- a/translations/id/4-Classification/README.md +++ b/translations/id/4-Classification/README.md @@ -1,12 +1,3 @@ - # Memulai dengan klasifikasi ## Topik regional: Masakan Asia dan India yang Lezat 🍜 diff --git a/translations/id/5-Clustering/1-Visualize/README.md b/translations/id/5-Clustering/1-Visualize/README.md index 53bff9c25..5f260cb64 100644 --- a/translations/id/5-Clustering/1-Visualize/README.md +++ b/translations/id/5-Clustering/1-Visualize/README.md @@ -1,12 +1,3 @@ - # Pengantar clustering Clustering adalah jenis [Pembelajaran Tanpa Pengawasan](https://wikipedia.org/wiki/Unsupervised_learning) yang mengasumsikan bahwa dataset tidak memiliki label atau inputnya tidak dipasangkan dengan output yang telah ditentukan sebelumnya. Clustering menggunakan berbagai algoritma untuk memilah data yang tidak berlabel dan memberikan pengelompokan berdasarkan pola yang ditemukan dalam data tersebut. diff --git a/translations/id/5-Clustering/1-Visualize/assignment.md b/translations/id/5-Clustering/1-Visualize/assignment.md index 7a6c34273..4222f8956 100644 --- a/translations/id/5-Clustering/1-Visualize/assignment.md +++ b/translations/id/5-Clustering/1-Visualize/assignment.md @@ -1,12 +1,3 @@ - # Penelitian visualisasi lain untuk clustering ## Instruksi diff --git a/translations/id/5-Clustering/1-Visualize/solution/Julia/README.md b/translations/id/5-Clustering/1-Visualize/solution/Julia/README.md index 7a453c67b..9a9cced84 100644 --- a/translations/id/5-Clustering/1-Visualize/solution/Julia/README.md +++ b/translations/id/5-Clustering/1-Visualize/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/id/5-Clustering/2-K-Means/README.md b/translations/id/5-Clustering/2-K-Means/README.md index 05807a74d..199c3e41e 100644 --- a/translations/id/5-Clustering/2-K-Means/README.md +++ b/translations/id/5-Clustering/2-K-Means/README.md @@ -1,12 +1,3 @@ - # K-Means clustering ## [Pre-lecture quiz](https://ff-quizzes.netlify.app/en/ml/) diff --git a/translations/id/5-Clustering/2-K-Means/assignment.md b/translations/id/5-Clustering/2-K-Means/assignment.md index c33ab82d0..f73b11a69 100644 --- a/translations/id/5-Clustering/2-K-Means/assignment.md +++ b/translations/id/5-Clustering/2-K-Means/assignment.md @@ -1,12 +1,3 @@ - # Coba metode clustering yang berbeda ## Instruksi diff --git a/translations/id/5-Clustering/2-K-Means/solution/Julia/README.md b/translations/id/5-Clustering/2-K-Means/solution/Julia/README.md index 57a710b55..9a9cced84 100644 --- a/translations/id/5-Clustering/2-K-Means/solution/Julia/README.md +++ b/translations/id/5-Clustering/2-K-Means/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/id/5-Clustering/README.md b/translations/id/5-Clustering/README.md index 5016e58d3..70118e873 100644 --- a/translations/id/5-Clustering/README.md +++ b/translations/id/5-Clustering/README.md @@ -1,12 +1,3 @@ - # Model Clustering untuk Pembelajaran Mesin Clustering adalah tugas pembelajaran mesin yang bertujuan untuk menemukan objek yang mirip satu sama lain dan mengelompokkannya ke dalam kelompok yang disebut cluster. Yang membedakan clustering dari pendekatan lain dalam pembelajaran mesin adalah bahwa prosesnya terjadi secara otomatis. Faktanya, bisa dikatakan bahwa ini adalah kebalikan dari pembelajaran terawasi. diff --git a/translations/id/6-NLP/1-Introduction-to-NLP/README.md b/translations/id/6-NLP/1-Introduction-to-NLP/README.md index 3d07410e1..70c343a92 100644 --- a/translations/id/6-NLP/1-Introduction-to-NLP/README.md +++ b/translations/id/6-NLP/1-Introduction-to-NLP/README.md @@ -1,12 +1,3 @@ - # Pengantar Pemrosesan Bahasa Alami Pelajaran ini mencakup sejarah singkat dan konsep penting dari *pemrosesan bahasa alami*, sebuah cabang dari *linguistik komputasional*. diff --git a/translations/id/6-NLP/1-Introduction-to-NLP/assignment.md b/translations/id/6-NLP/1-Introduction-to-NLP/assignment.md index 6216f09cb..e9617e873 100644 --- a/translations/id/6-NLP/1-Introduction-to-NLP/assignment.md +++ b/translations/id/6-NLP/1-Introduction-to-NLP/assignment.md @@ -1,12 +1,3 @@ - # Cari Bot ## Instruksi diff --git a/translations/id/6-NLP/2-Tasks/README.md b/translations/id/6-NLP/2-Tasks/README.md index fd556a953..44ac7d3e2 100644 --- a/translations/id/6-NLP/2-Tasks/README.md +++ b/translations/id/6-NLP/2-Tasks/README.md @@ -1,12 +1,3 @@ - # Tugas dan Teknik Pemrosesan Bahasa Alami yang Umum Untuk sebagian besar *pemrosesan bahasa alami*, teks yang akan diproses harus dipecah, diperiksa, dan hasilnya disimpan atau dibandingkan dengan aturan dan kumpulan data. Tugas-tugas ini memungkinkan programmer untuk mendapatkan _makna_ atau _niat_ atau hanya _frekuensi_ istilah dan kata dalam sebuah teks. diff --git a/translations/id/6-NLP/2-Tasks/assignment.md b/translations/id/6-NLP/2-Tasks/assignment.md index f9e4958f6..1ffccb306 100644 --- a/translations/id/6-NLP/2-Tasks/assignment.md +++ b/translations/id/6-NLP/2-Tasks/assignment.md @@ -1,12 +1,3 @@ - # Membuat Bot Menjawab ## Instruksi diff --git a/translations/id/6-NLP/3-Translation-Sentiment/README.md b/translations/id/6-NLP/3-Translation-Sentiment/README.md index 07f9f82d0..361743a10 100644 --- a/translations/id/6-NLP/3-Translation-Sentiment/README.md +++ b/translations/id/6-NLP/3-Translation-Sentiment/README.md @@ -1,12 +1,3 @@ - # Analisis Sentimen dan Terjemahan dengan ML Dalam pelajaran sebelumnya, Anda telah belajar cara membangun bot dasar menggunakan `TextBlob`, sebuah pustaka yang mengintegrasikan ML di balik layar untuk melakukan tugas NLP dasar seperti ekstraksi frasa kata benda. Tantangan penting lainnya dalam linguistik komputasi adalah _terjemahan_ yang akurat dari satu bahasa lisan atau tulisan ke bahasa lain. diff --git a/translations/id/6-NLP/3-Translation-Sentiment/assignment.md b/translations/id/6-NLP/3-Translation-Sentiment/assignment.md index 0981c14fe..49426b2ea 100644 --- a/translations/id/6-NLP/3-Translation-Sentiment/assignment.md +++ b/translations/id/6-NLP/3-Translation-Sentiment/assignment.md @@ -1,12 +1,3 @@ - # Lisensi Puitis ## Instruksi diff --git a/translations/id/6-NLP/3-Translation-Sentiment/solution/Julia/README.md b/translations/id/6-NLP/3-Translation-Sentiment/solution/Julia/README.md index 91360ba1e..1043dc23e 100644 --- a/translations/id/6-NLP/3-Translation-Sentiment/solution/Julia/README.md +++ b/translations/id/6-NLP/3-Translation-Sentiment/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/id/6-NLP/3-Translation-Sentiment/solution/R/README.md b/translations/id/6-NLP/3-Translation-Sentiment/solution/R/README.md index b9f8327f6..814f0a054 100644 --- a/translations/id/6-NLP/3-Translation-Sentiment/solution/R/README.md +++ b/translations/id/6-NLP/3-Translation-Sentiment/solution/R/README.md @@ -1,12 +1,3 @@ - ini adalah tempat sementara --- diff --git a/translations/id/6-NLP/4-Hotel-Reviews-1/README.md b/translations/id/6-NLP/4-Hotel-Reviews-1/README.md index eb9be50f8..2b6baa736 100644 --- a/translations/id/6-NLP/4-Hotel-Reviews-1/README.md +++ b/translations/id/6-NLP/4-Hotel-Reviews-1/README.md @@ -1,12 +1,3 @@ - # Analisis Sentimen dengan Ulasan Hotel - Memproses Data Di bagian ini, Anda akan menggunakan teknik yang telah dipelajari di pelajaran sebelumnya untuk melakukan analisis data eksplorasi pada dataset besar. Setelah memahami kegunaan berbagai kolom, Anda akan belajar: diff --git a/translations/id/6-NLP/4-Hotel-Reviews-1/assignment.md b/translations/id/6-NLP/4-Hotel-Reviews-1/assignment.md index c7abd144d..a25c642ec 100644 --- a/translations/id/6-NLP/4-Hotel-Reviews-1/assignment.md +++ b/translations/id/6-NLP/4-Hotel-Reviews-1/assignment.md @@ -1,12 +1,3 @@ - # NLTK ## Instruksi diff --git a/translations/id/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md b/translations/id/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md index e8fb937a8..9a9cced84 100644 --- a/translations/id/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md +++ b/translations/id/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/id/6-NLP/4-Hotel-Reviews-1/solution/R/README.md b/translations/id/6-NLP/4-Hotel-Reviews-1/solution/R/README.md index f83cee00d..5cc47d173 100644 --- a/translations/id/6-NLP/4-Hotel-Reviews-1/solution/R/README.md +++ b/translations/id/6-NLP/4-Hotel-Reviews-1/solution/R/README.md @@ -1,12 +1,3 @@ - ini adalah tempat sementara --- diff --git a/translations/id/6-NLP/5-Hotel-Reviews-2/README.md b/translations/id/6-NLP/5-Hotel-Reviews-2/README.md index 0ae9190ba..625f87987 100644 --- a/translations/id/6-NLP/5-Hotel-Reviews-2/README.md +++ b/translations/id/6-NLP/5-Hotel-Reviews-2/README.md @@ -1,12 +1,3 @@ - # Analisis Sentimen dengan Ulasan Hotel Setelah Anda menjelajahi dataset secara mendetail, sekarang saatnya untuk memfilter kolom dan menggunakan teknik NLP pada dataset untuk mendapatkan wawasan baru tentang hotel. diff --git a/translations/id/6-NLP/5-Hotel-Reviews-2/assignment.md b/translations/id/6-NLP/5-Hotel-Reviews-2/assignment.md index bf0ef2b94..9a8cf2668 100644 --- a/translations/id/6-NLP/5-Hotel-Reviews-2/assignment.md +++ b/translations/id/6-NLP/5-Hotel-Reviews-2/assignment.md @@ -1,12 +1,3 @@ - # Coba dataset yang berbeda ## Instruksi diff --git a/translations/id/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md b/translations/id/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md index 486466dde..165735330 100644 --- a/translations/id/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md +++ b/translations/id/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/id/6-NLP/5-Hotel-Reviews-2/solution/R/README.md b/translations/id/6-NLP/5-Hotel-Reviews-2/solution/R/README.md index 841ccb111..5cc47d173 100644 --- a/translations/id/6-NLP/5-Hotel-Reviews-2/solution/R/README.md +++ b/translations/id/6-NLP/5-Hotel-Reviews-2/solution/R/README.md @@ -1,12 +1,3 @@ - ini adalah tempat sementara --- diff --git a/translations/id/6-NLP/README.md b/translations/id/6-NLP/README.md index dfe80945b..48f5e46ea 100644 --- a/translations/id/6-NLP/README.md +++ b/translations/id/6-NLP/README.md @@ -1,12 +1,3 @@ - # Memulai dengan pemrosesan bahasa alami Pemrosesan bahasa alami (NLP) adalah kemampuan program komputer untuk memahami bahasa manusia sebagaimana diucapkan dan ditulis -- yang disebut sebagai bahasa alami. Ini adalah komponen dari kecerdasan buatan (AI). NLP telah ada selama lebih dari 50 tahun dan memiliki akar dalam bidang linguistik. Seluruh bidang ini diarahkan untuk membantu mesin memahami dan memproses bahasa manusia. Hal ini kemudian dapat digunakan untuk melakukan tugas-tugas seperti pemeriksaan ejaan atau terjemahan mesin. NLP memiliki berbagai aplikasi dunia nyata di sejumlah bidang, termasuk penelitian medis, mesin pencari, dan intelijen bisnis. diff --git a/translations/id/6-NLP/data/README.md b/translations/id/6-NLP/data/README.md index ca020612f..fb20fc3eb 100644 --- a/translations/id/6-NLP/data/README.md +++ b/translations/id/6-NLP/data/README.md @@ -1,12 +1,3 @@ - Unduh data ulasan hotel ke folder ini. --- diff --git a/translations/id/7-TimeSeries/1-Introduction/README.md b/translations/id/7-TimeSeries/1-Introduction/README.md index e492a01c4..d5e5df069 100644 --- a/translations/id/7-TimeSeries/1-Introduction/README.md +++ b/translations/id/7-TimeSeries/1-Introduction/README.md @@ -1,12 +1,3 @@ - # Pengantar Peramalan Deret Waktu ![Ringkasan deret waktu dalam sketchnote](../../../../sketchnotes/ml-timeseries.png) diff --git a/translations/id/7-TimeSeries/1-Introduction/assignment.md b/translations/id/7-TimeSeries/1-Introduction/assignment.md index be62ee608..6013d406a 100644 --- a/translations/id/7-TimeSeries/1-Introduction/assignment.md +++ b/translations/id/7-TimeSeries/1-Introduction/assignment.md @@ -1,12 +1,3 @@ - # Visualisasikan Beberapa Lagi Deret Waktu ## Instruksi diff --git a/translations/id/7-TimeSeries/1-Introduction/solution/Julia/README.md b/translations/id/7-TimeSeries/1-Introduction/solution/Julia/README.md index 01053e818..9a9cced84 100644 --- a/translations/id/7-TimeSeries/1-Introduction/solution/Julia/README.md +++ b/translations/id/7-TimeSeries/1-Introduction/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/id/7-TimeSeries/1-Introduction/solution/R/README.md b/translations/id/7-TimeSeries/1-Introduction/solution/R/README.md index 7de64af6e..5cc47d173 100644 --- a/translations/id/7-TimeSeries/1-Introduction/solution/R/README.md +++ b/translations/id/7-TimeSeries/1-Introduction/solution/R/README.md @@ -1,12 +1,3 @@ - ini adalah tempat sementara --- diff --git a/translations/id/7-TimeSeries/2-ARIMA/README.md b/translations/id/7-TimeSeries/2-ARIMA/README.md index aa1a04f81..4641358ee 100644 --- a/translations/id/7-TimeSeries/2-ARIMA/README.md +++ b/translations/id/7-TimeSeries/2-ARIMA/README.md @@ -1,12 +1,3 @@ - # Peramalan Deret Waktu dengan ARIMA Pada pelajaran sebelumnya, Anda telah mempelajari sedikit tentang peramalan deret waktu dan memuat dataset yang menunjukkan fluktuasi beban listrik selama periode waktu tertentu. diff --git a/translations/id/7-TimeSeries/2-ARIMA/assignment.md b/translations/id/7-TimeSeries/2-ARIMA/assignment.md index 16823fbaa..b2a6d342e 100644 --- a/translations/id/7-TimeSeries/2-ARIMA/assignment.md +++ b/translations/id/7-TimeSeries/2-ARIMA/assignment.md @@ -1,12 +1,3 @@ - # Model ARIMA Baru ## Instruksi diff --git a/translations/id/7-TimeSeries/2-ARIMA/solution/Julia/README.md b/translations/id/7-TimeSeries/2-ARIMA/solution/Julia/README.md index e129c4b53..9a9cced84 100644 --- a/translations/id/7-TimeSeries/2-ARIMA/solution/Julia/README.md +++ b/translations/id/7-TimeSeries/2-ARIMA/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/id/7-TimeSeries/2-ARIMA/solution/R/README.md b/translations/id/7-TimeSeries/2-ARIMA/solution/R/README.md index 2f5e03950..5cc47d173 100644 --- a/translations/id/7-TimeSeries/2-ARIMA/solution/R/README.md +++ b/translations/id/7-TimeSeries/2-ARIMA/solution/R/README.md @@ -1,12 +1,3 @@ - ini adalah tempat sementara --- diff --git a/translations/id/7-TimeSeries/3-SVR/README.md b/translations/id/7-TimeSeries/3-SVR/README.md index f734c9da6..2f7348458 100644 --- a/translations/id/7-TimeSeries/3-SVR/README.md +++ b/translations/id/7-TimeSeries/3-SVR/README.md @@ -1,12 +1,3 @@ - # Peramalan Deret Waktu dengan Support Vector Regressor Pada pelajaran sebelumnya, Anda telah mempelajari cara menggunakan model ARIMA untuk membuat prediksi deret waktu. Sekarang Anda akan mempelajari model Support Vector Regressor, yaitu model regresi yang digunakan untuk memprediksi data kontinu. diff --git a/translations/id/7-TimeSeries/3-SVR/assignment.md b/translations/id/7-TimeSeries/3-SVR/assignment.md index 738f0b6d2..95218b3da 100644 --- a/translations/id/7-TimeSeries/3-SVR/assignment.md +++ b/translations/id/7-TimeSeries/3-SVR/assignment.md @@ -1,12 +1,3 @@ - # Model SVR Baru ## Instruksi [^1] diff --git a/translations/id/7-TimeSeries/README.md b/translations/id/7-TimeSeries/README.md index a974b959b..c0ec85733 100644 --- a/translations/id/7-TimeSeries/README.md +++ b/translations/id/7-TimeSeries/README.md @@ -1,12 +1,3 @@ - # Pengantar Peramalan Deret Waktu Apa itu peramalan deret waktu? Ini adalah tentang memprediksi kejadian di masa depan dengan menganalisis tren dari masa lalu. diff --git a/translations/id/8-Reinforcement/1-QLearning/README.md b/translations/id/8-Reinforcement/1-QLearning/README.md index bb588fa49..d8133430f 100644 --- a/translations/id/8-Reinforcement/1-QLearning/README.md +++ b/translations/id/8-Reinforcement/1-QLearning/README.md @@ -1,12 +1,3 @@ - # Pengantar Pembelajaran Penguatan dan Q-Learning ![Ringkasan pembelajaran penguatan dalam pembelajaran mesin dalam bentuk sketchnote](../../../../sketchnotes/ml-reinforcement.png) diff --git a/translations/id/8-Reinforcement/1-QLearning/assignment.md b/translations/id/8-Reinforcement/1-QLearning/assignment.md index cf6166023..2f5bd839a 100644 --- a/translations/id/8-Reinforcement/1-QLearning/assignment.md +++ b/translations/id/8-Reinforcement/1-QLearning/assignment.md @@ -1,12 +1,3 @@ - # Dunia yang Lebih Realistis Dalam situasi kita, Peter dapat bergerak hampir tanpa merasa lelah atau lapar. Dalam dunia yang lebih realistis, dia harus duduk dan beristirahat dari waktu ke waktu, serta memberi makan dirinya sendiri. Mari kita buat dunia kita lebih realistis dengan menerapkan aturan berikut: diff --git a/translations/id/8-Reinforcement/1-QLearning/solution/Julia/README.md b/translations/id/8-Reinforcement/1-QLearning/solution/Julia/README.md index dc40d78e4..9a9cced84 100644 --- a/translations/id/8-Reinforcement/1-QLearning/solution/Julia/README.md +++ b/translations/id/8-Reinforcement/1-QLearning/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/id/8-Reinforcement/1-QLearning/solution/R/README.md b/translations/id/8-Reinforcement/1-QLearning/solution/R/README.md index 591e99986..5cc47d173 100644 --- a/translations/id/8-Reinforcement/1-QLearning/solution/R/README.md +++ b/translations/id/8-Reinforcement/1-QLearning/solution/R/README.md @@ -1,12 +1,3 @@ - ini adalah tempat sementara --- diff --git a/translations/id/8-Reinforcement/2-Gym/README.md b/translations/id/8-Reinforcement/2-Gym/README.md index c0cad0f29..0760019b7 100644 --- a/translations/id/8-Reinforcement/2-Gym/README.md +++ b/translations/id/8-Reinforcement/2-Gym/README.md @@ -1,12 +1,3 @@ - ## Prasyarat Dalam pelajaran ini, kita akan menggunakan pustaka bernama **OpenAI Gym** untuk mensimulasikan berbagai **lingkungan**. Anda dapat menjalankan kode pelajaran ini secara lokal (misalnya dari Visual Studio Code), di mana simulasi akan terbuka di jendela baru. Saat menjalankan kode secara online, Anda mungkin perlu melakukan beberapa penyesuaian pada kode, seperti yang dijelaskan [di sini](https://towardsdatascience.com/rendering-openai-gym-envs-on-binder-and-google-colab-536f99391cc7). diff --git a/translations/id/8-Reinforcement/2-Gym/assignment.md b/translations/id/8-Reinforcement/2-Gym/assignment.md index eff91a7be..869285f2f 100644 --- a/translations/id/8-Reinforcement/2-Gym/assignment.md +++ b/translations/id/8-Reinforcement/2-Gym/assignment.md @@ -1,12 +1,3 @@ - # Melatih Mountain Car [OpenAI Gym](http://gym.openai.com) dirancang sedemikian rupa sehingga semua lingkungan menyediakan API yang sama - yaitu metode yang sama `reset`, `step`, dan `render`, serta abstraksi yang sama untuk **action space** dan **observation space**. Oleh karena itu, seharusnya memungkinkan untuk mengadaptasi algoritma pembelajaran penguatan yang sama ke berbagai lingkungan dengan perubahan kode yang minimal. diff --git a/translations/id/8-Reinforcement/2-Gym/solution/Julia/README.md b/translations/id/8-Reinforcement/2-Gym/solution/Julia/README.md index 0324d9751..9a9cced84 100644 --- a/translations/id/8-Reinforcement/2-Gym/solution/Julia/README.md +++ b/translations/id/8-Reinforcement/2-Gym/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/id/8-Reinforcement/2-Gym/solution/R/README.md b/translations/id/8-Reinforcement/2-Gym/solution/R/README.md index 2a256c25f..814f0a054 100644 --- a/translations/id/8-Reinforcement/2-Gym/solution/R/README.md +++ b/translations/id/8-Reinforcement/2-Gym/solution/R/README.md @@ -1,12 +1,3 @@ - ini adalah tempat sementara --- diff --git a/translations/id/8-Reinforcement/README.md b/translations/id/8-Reinforcement/README.md index 3a6bfa38b..70f945d58 100644 --- a/translations/id/8-Reinforcement/README.md +++ b/translations/id/8-Reinforcement/README.md @@ -1,12 +1,3 @@ - # Pengantar Pembelajaran Penguatan Pembelajaran penguatan, atau RL, dianggap sebagai salah satu paradigma dasar pembelajaran mesin, selain pembelajaran terawasi dan pembelajaran tak terawasi. RL berfokus pada pengambilan keputusan: membuat keputusan yang tepat atau setidaknya belajar dari keputusan tersebut. diff --git a/translations/id/9-Real-World/1-Applications/README.md b/translations/id/9-Real-World/1-Applications/README.md index 564fb6e5f..74f88f2d1 100644 --- a/translations/id/9-Real-World/1-Applications/README.md +++ b/translations/id/9-Real-World/1-Applications/README.md @@ -1,12 +1,3 @@ - # Postscript: Pembelajaran Mesin di Dunia Nyata ![Ringkasan pembelajaran mesin di dunia nyata dalam bentuk sketchnote](../../../../sketchnotes/ml-realworld.png) diff --git a/translations/id/9-Real-World/1-Applications/assignment.md b/translations/id/9-Real-World/1-Applications/assignment.md index 1e2ea61ae..0d5fd3c32 100644 --- a/translations/id/9-Real-World/1-Applications/assignment.md +++ b/translations/id/9-Real-World/1-Applications/assignment.md @@ -1,12 +1,3 @@ - # Perburuan ML ## Instruksi diff --git a/translations/id/9-Real-World/2-Debugging-ML-Models/README.md b/translations/id/9-Real-World/2-Debugging-ML-Models/README.md index a977470bd..098b7070d 100644 --- a/translations/id/9-Real-World/2-Debugging-ML-Models/README.md +++ b/translations/id/9-Real-World/2-Debugging-ML-Models/README.md @@ -1,12 +1,3 @@ - # Postscript: Debugging Model dalam Pembelajaran Mesin menggunakan Komponen Dasbor AI yang Bertanggung Jawab ## [Kuis pra-kuliah](https://ff-quizzes.netlify.app/en/ml/) diff --git a/translations/id/9-Real-World/2-Debugging-ML-Models/assignment.md b/translations/id/9-Real-World/2-Debugging-ML-Models/assignment.md index 4d71bd403..3480c8aeb 100644 --- a/translations/id/9-Real-World/2-Debugging-ML-Models/assignment.md +++ b/translations/id/9-Real-World/2-Debugging-ML-Models/assignment.md @@ -1,12 +1,3 @@ - # Jelajahi Dasbor Responsible AI (RAI) ## Instruksi diff --git a/translations/id/9-Real-World/README.md b/translations/id/9-Real-World/README.md index f2447edb9..009b40f32 100644 --- a/translations/id/9-Real-World/README.md +++ b/translations/id/9-Real-World/README.md @@ -1,12 +1,3 @@ - # Postscript: Aplikasi Dunia Nyata dari Pembelajaran Mesin Klasik Dalam bagian kurikulum ini, Anda akan diperkenalkan dengan beberapa aplikasi dunia nyata dari pembelajaran mesin klasik. Kami telah menjelajahi internet untuk menemukan makalah dan artikel tentang aplikasi yang menggunakan strategi ini, dengan menghindari jaringan saraf, pembelajaran mendalam, dan AI sejauh mungkin. Pelajari bagaimana pembelajaran mesin digunakan dalam sistem bisnis, aplikasi ekologi, keuangan, seni dan budaya, serta lainnya. diff --git a/translations/id/AGENTS.md b/translations/id/AGENTS.md index 032fbdbf2..be8de5e95 100644 --- a/translations/id/AGENTS.md +++ b/translations/id/AGENTS.md @@ -1,12 +1,3 @@ - # AGENTS.md ## Gambaran Proyek diff --git a/translations/id/CODE_OF_CONDUCT.md b/translations/id/CODE_OF_CONDUCT.md index b496744d6..ebaecd530 100644 --- a/translations/id/CODE_OF_CONDUCT.md +++ b/translations/id/CODE_OF_CONDUCT.md @@ -1,12 +1,3 @@ - # Kode Etik Sumber Terbuka Microsoft Proyek ini telah mengadopsi [Kode Etik Sumber Terbuka Microsoft](https://opensource.microsoft.com/codeofconduct/). diff --git a/translations/id/CONTRIBUTING.md b/translations/id/CONTRIBUTING.md index 88b33acbf..da6c307b6 100644 --- a/translations/id/CONTRIBUTING.md +++ b/translations/id/CONTRIBUTING.md @@ -1,12 +1,3 @@ - # Berkontribusi Proyek ini menyambut kontribusi dan saran. Sebagian besar kontribusi mengharuskan Anda diff --git a/translations/id/README.md b/translations/id/README.md index 66352bbd7..bbef42372 100644 --- a/translations/id/README.md +++ b/translations/id/README.md @@ -1,12 +1,3 @@ - [![GitHub license](https://img.shields.io/github/license/microsoft/ML-For-Beginners.svg)](https://github.com/microsoft/ML-For-Beginners/blob/master/LICENSE) [![GitHub contributors](https://img.shields.io/github/contributors/microsoft/ML-For-Beginners.svg)](https://GitHub.com/microsoft/ML-For-Beginners/graphs/contributors/) [![GitHub issues](https://img.shields.io/github/issues/microsoft/ML-For-Beginners.svg)](https://GitHub.com/microsoft/ML-For-Beginners/issues/) @@ -22,11 +13,11 @@ CO_OP_TRANSLATOR_METADATA: #### Didukung melalui GitHub Action (Otomatis & Selalu Terbaru) -[Arabic](../ar/README.md) | [Bengali](../bn/README.md) | [Bulgarian](../bg/README.md) | [Burmese (Myanmar)](../my/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Croatian](../hr/README.md) | [Czech](../cs/README.md) | [Danish](../da/README.md) | [Dutch](../nl/README.md) | [Estonian](../et/README.md) | [Finnish](../fi/README.md) | [French](../fr/README.md) | [German](../de/README.md) | [Greek](../el/README.md) | [Hebrew](../he/README.md) | [Hindi](../hi/README.md) | [Hungarian](../hu/README.md) | [Indonesian](./README.md) | [Italian](../it/README.md) | [Japanese](../ja/README.md) | [Kannada](../kn/README.md) | [Korean](../ko/README.md) | [Lithuanian](../lt/README.md) | [Malay](../ms/README.md) | [Malayalam](../ml/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Nigerian Pidgin](../pcm/README.md) | [Norwegian](../no/README.md) | [Persian (Farsi)](../fa/README.md) | [Polish](../pl/README.md) | [Portuguese (Brazil)](../br/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Romanian](../ro/README.md) | [Russian](../ru/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Slovak](../sk/README.md) | [Slovenian](../sl/README.md) | [Spanish](../es/README.md) | [Swahili](../sw/README.md) | [Swedish](../sv/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Tamil](../ta/README.md) | [Telugu](../te/README.md) | [Thai](../th/README.md) | [Turkish](../tr/README.md) | [Ukrainian](../uk/README.md) | [Urdu](../ur/README.md) | [Vietnamese](../vi/README.md) +[Arab](../ar/README.md) | [Bengali](../bn/README.md) | [Bulgaria](../bg/README.md) | [Burma (Myanmar)](../my/README.md) | [Tionghoa (Sederhana)](../zh-CN/README.md) | [Tionghoa (Tradisional, Hong Kong)](../zh-HK/README.md) | [Tionghoa (Tradisional, Macau)](../zh-MO/README.md) | [Tionghoa (Tradisional, Taiwan)](../zh-TW/README.md) | [Kroasia](../hr/README.md) | [Ceko](../cs/README.md) | [Denmark](../da/README.md) | [Belanda](../nl/README.md) | [Estonia](../et/README.md) | [Finlandia](../fi/README.md) | [Perancis](../fr/README.md) | [Jerman](../de/README.md) | [Yunani](../el/README.md) | [Ibrani](../he/README.md) | [Hindi](../hi/README.md) | [Hungaria](../hu/README.md) | [Indonesia](./README.md) | [Italia](../it/README.md) | [Jepang](../ja/README.md) | [Kannada](../kn/README.md) | [Korea](../ko/README.md) | [Lituania](../lt/README.md) | [Melayu](../ms/README.md) | [Malayalam](../ml/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Nigerian Pidgin](../pcm/README.md) | [Norwegia](../no/README.md) | [Persia (Farsi)](../fa/README.md) | [Polandia](../pl/README.md) | [Portugis (Brasil)](../pt-BR/README.md) | [Portugis (Portugal)](../pt-PT/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Rumania](../ro/README.md) | [Rusia](../ru/README.md) | [Serbia (Sirilik)](../sr/README.md) | [Slovakia](../sk/README.md) | [Slovenia](../sl/README.md) | [Spanyol](../es/README.md) | [Swahili](../sw/README.md) | [Swedia](../sv/README.md) | [Tagalog (Filipina)](../tl/README.md) | [Tamil](../ta/README.md) | [Telugu](../te/README.md) | [Thai](../th/README.md) | [Turki](../tr/README.md) | [Ukraina](../uk/README.md) | [Urdu](../ur/README.md) | [Vietnam](../vi/README.md) -> **Lebih suka Mengkloning Secara Lokal?** +> **Lebih suka Clone Lokal?** -> Repositori ini mencakup lebih dari 50 terjemahan bahasa yang secara signifikan meningkatkan ukuran unduhan. Untuk mengkloning tanpa terjemahan, gunakan sparse checkout: +> Repositori ini mencakup lebih dari 50 terjemahan bahasa yang secara signifikan meningkatkan ukuran unduhan. Untuk clone tanpa terjemahan, gunakan sparse checkout: > ```bash > git clone --filter=blob:none --sparse https://github.com/microsoft/ML-For-Beginners.git > cd ML-For-Beginners @@ -35,62 +26,62 @@ CO_OP_TRANSLATOR_METADATA: > Ini memberi Anda semua yang Anda butuhkan untuk menyelesaikan kursus dengan unduhan yang jauh lebih cepat. -#### Bergabunglah dengan Komunitas Kami +#### Bergabung dengan Komunitas Kami [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -Kami memiliki seri belajar dengan AI di Discord, pelajari lebih lanjut dan bergabunglah bersama kami di [Learn with AI Series](https://aka.ms/learnwithai/discord) dari 18 - 30 September, 2025. Anda akan mendapatkan tips dan trik menggunakan GitHub Copilot untuk Data Science. +Kami memiliki seri belajar Discord dengan AI yang sedang berlangsung, pelajari lebih lanjut dan bergabunglah dengan kami di [Learn with AI Series](https://aka.ms/learnwithai/discord) mulai 18 - 30 September 2025. Anda akan mendapatkan tips dan trik menggunakan GitHub Copilot untuk Data Science. -![Learn with AI series](../../../../translated_images/id/3.9b58fd8d6c373c20.webp) +![Learn with AI series](../../translated_images/id/3.9b58fd8d6c373c20.webp) -# Machine Learning untuk Pemula - Kurikulum +# Pembelajaran Mesin untuk Pemula - Kurikulum -> 🌍 Jelajahi dunia saat kita mengeksplorasi Machine Learning melalui budaya dunia 🌍 +> 🌍 Jelajahi dunia sambil mempelajari Pembelajaran Mesin melalui budaya dunia 🌍 -Cloud Advocates di Microsoft dengan bangga menawarkan kurikulum 12-minggu, 26-pelajaran yang membahas **Machine Learning**. Dalam kurikulum ini, Anda akan belajar tentang apa yang kadang disebut **machine learning klasik**, menggunakan terutama perpustakaan Scikit-learn dan menghindari pembelajaran mendalam, yang dibahas dalam [kurikulum AI untuk Pemula](https://aka.ms/ai4beginners). Padu padankan pelajaran ini dengan kurikulum ['Data Science untuk Pemula'](https://aka.ms/ds4beginners), juga! +Cloud Advocates di Microsoft dengan bangga menawarkan kurikulum 12 minggu, 26 pelajaran yang semuanya membahas **Pembelajaran Mesin**. Dalam kurikulum ini, Anda akan belajar tentang apa yang kadang disebut **pembelajaran mesin klasik**, yang terutama menggunakan Scikit-learn sebagai perpustakaan dan menghindari pembelajaran mendalam, yang dibahas dalam [kurikulum AI untuk Pemula kami](https://aka.ms/ai4beginners). Padukan pelajaran ini dengan kurikulum ['Data Science untuk Pemula'](https://aka.ms/ds4beginners), juga! -Jelajahi bersama kami ke berbagai belahan dunia saat kami menerapkan teknik klasik ini pada data dari berbagai wilayah di dunia. Setiap pelajaran mencakup kuis sebelum dan sesudah pelajaran, instruksi tertulis untuk menyelesaikan pelajaran, solusi, tugas, dan lainnya. Pendekatan berbasis proyek memungkinkan Anda belajar sambil membangun, cara efektif agar keterampilan baru 'bersemangat'. +Jelajahi bersama kami dari berbagai belahan dunia saat kami menerapkan teknik klasik ini pada data dari banyak wilayah di dunia. Setiap pelajaran mencakup kuis pra- dan pasca-pelajaran, instruksi tertulis untuk menyelesaikan pelajaran, solusi, tugas, dan lainnya. Pedagogi berbasis proyek kami memungkinkan Anda belajar sambil membangun, cara yang terbukti efektif untuk membuat keterampilan baru 'melekat'. -**✍️ Terima kasih sebesar-besarnya kepada penulis kami** Jen Looper, Stephen Howell, Francesca Lazzeri, Tomomi Imura, Cassie Breviu, Dmitry Soshnikov, Chris Noring, Anirban Mukherjee, Ornella Altunyan, Ruth Yakubu dan Amy Boyd +**✍️ Terima kasih sebesar-besarnya kepada para penulis kami** Jen Looper, Stephen Howell, Francesca Lazzeri, Tomomi Imura, Cassie Breviu, Dmitry Soshnikov, Chris Noring, Anirban Mukherjee, Ornella Altunyan, Ruth Yakubu, dan Amy Boyd -**🎨 Terima kasih juga kepada ilustrator kami** Tomomi Imura, Dasani Madipalli, dan Jen Looper +**🎨 Terima kasih juga kepada para ilustrator kami** Tomomi Imura, Dasani Madipalli, dan Jen Looper -**🙏 Terima kasih khusus 🙏 kepada penulis, pengulas, dan kontributor konten Microsoft Student Ambassador kami**, khususnya Rishit Dagli, Muhammad Sakib Khan Inan, Rohan Raj, Alexandru Petrescu, Abhishek Jaiswal, Nawrin Tabassum, Ioan Samuila, dan Snigdha Agarwal +**🙏 Terima kasih khusus 🙏 kepada para Microsoft Student Ambassador penulis, pengulas, dan kontributor konten kami**, terutama Rishit Dagli, Muhammad Sakib Khan Inan, Rohan Raj, Alexandru Petrescu, Abhishek Jaiswal, Nawrin Tabassum, Ioan Samuila, dan Snigdha Agarwal **🤩 Terima kasih ekstra kepada Microsoft Student Ambassadors Eric Wanjau, Jasleen Sondhi, dan Vidushi Gupta untuk pelajaran R kami!** # Memulai -Ikuti langkah-langkah ini: -1. **Fork Repositori**: Klik tombol "Fork" di sudut kanan atas halaman ini. +Ikuti langkah-langkah berikut: +1. **Fork Repositori**: Klik tombol "Fork" di pojok kanan atas halaman ini. 2. **Clone Repositori**: `git clone https://github.com/microsoft/ML-For-Beginners.git` -> [temukan semua sumber daya tambahan untuk kursus ini di koleksi Microsoft Learn kami](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) +> [temukan semua sumber tambahan untuk kursus ini dalam koleksi Microsoft Learn kami](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) -> 🔧 **Butuh bantuan?** Periksa [Panduan Pemecahan Masalah](TROUBLESHOOTING.md) kami untuk solusi masalah umum dengan pemasangan, penyiapan, dan menjalankan pelajaran. +> 🔧 **Butuh bantuan?** Periksa [Panduan Pemecahan Masalah](TROUBLESHOOTING.md) kami untuk solusi masalah umum dengan instalasi, pengaturan, dan menjalankan pelajaran. -**[Siswa](https://aka.ms/student-page)**, untuk menggunakan kurikulum ini, fork seluruh repo ke akun GitHub Anda sendiri dan selesaikan latihan secara mandiri atau dalam kelompok: +**[Siswa](https://aka.ms/student-page)**, untuk menggunakan kurikulum ini, fork seluruh repo ke akun GitHub Anda dan selesaikan latihan secara mandiri atau bersama kelompok: -- Mulai dengan kuis pemanasan sebelum kuliah. -- Baca kuliah dan selesaikan aktivitas, berhenti dan renungkan setiap pemeriksaan pengetahuan. -- Coba buat proyek dengan memahami pelajaran daripada langsung menjalankan kode solusi; tetapi kode tersebut tersedia di folder `/solution` pada setiap pelajaran berbasis proyek. -- Ikuti kuis setelah kuliah. +- Mulai dengan kuis pra-ceramah. +- Baca ceramah dan selesaikan aktivitas, berhenti sejenak dan renungkan pada setiap cek pengetahuan. +- Cobalah membuat proyek dengan memahami pelajaran, bukan hanya menjalankan kode solusi; kode tersebut tersedia di folder `/solution` di setiap pelajaran berbasis proyek. +- Ikuti kuis pasca-ceramah. - Selesaikan tantangan. - Selesaikan tugas. -- Setelah menyelesaikan satu kelompok pelajaran, kunjungi [Papan Diskusi](https://github.com/microsoft/ML-For-Beginners/discussions) dan "belajar secara terbuka" dengan mengisi rubrik PAT yang sesuai. 'PAT' adalah Alat Penilaian Kemajuan yang merupakan rubrik yang Anda isi untuk memperdalam pembelajaran Anda. Anda juga dapat merespon PAT lain agar kita bisa belajar bersama. +- Setelah menyelesaikan kelompok pelajaran, kunjungi [Papan Diskusi](https://github.com/microsoft/ML-For-Beginners/discussions) dan "belajar dengan lantang" dengan mengisi rubrik PAT yang sesuai. 'PAT' adalah Alat Penilaian Kemajuan yang merupakan rubrik yang Anda isi untuk memperdalam pembelajaran. Anda juga dapat bereaksi terhadap PAT lain agar kita belajar bersama. -> Untuk studi lanjutan, kami sarankan mengikuti modul dan jalur belajar [Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/k7o7tg1gp306q4?WT.mc_id=academic-77952-leestott) ini. +> Untuk studi lebih lanjut, kami sarankan mengikuti modul dan jalur pembelajaran [Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/k7o7tg1gp306q4?WT.mc_id=academic-77952-leestott). -**Guru**, kami telah [menyediakan beberapa saran](for-teachers.md) tentang cara menggunakan kurikulum ini. +**Guru**, kami telah [menyertakan beberapa saran](for-teachers.md) tentang cara menggunakan kurikulum ini. --- -## Video panduan +## Video penjelasan -Beberapa pelajaran tersedia dalam bentuk video singkat. Anda dapat menemukannya secara inline di pelajaran, atau di [playlist ML untuk Pemula di saluran YouTube Microsoft Developer](https://aka.ms/ml-beginners-videos) dengan mengklik gambar di bawah ini. +Beberapa pelajaran tersedia dalam bentuk video pendek. Anda dapat menemukan semuanya di dalam pelajaran, atau pada [playlist ML for Beginners di channel Microsoft Developer YouTube](https://aka.ms/ml-beginners-videos) dengan mengklik gambar di bawah ini. -[![ML for beginners banner](../../../../translated_images/id/ml-for-beginners-video-banner.63f694a100034bc6.webp)](https://aka.ms/ml-beginners-videos) +[![ML for beginners banner](../../translated_images/id/ml-for-beginners-video-banner.63f694a100034bc6.webp)](https://aka.ms/ml-beginners-videos) --- @@ -100,96 +91,97 @@ Beberapa pelajaran tersedia dalam bentuk video singkat. Anda dapat menemukannya **Gif oleh** [Mohit Jaisal](https://linkedin.com/in/mohitjaisal) -> 🎥 Klik gambar di atas untuk video tentang proyek dan orang-orang yang membuatnya! +> 🎥 Klik gambar di atas untuk video tentang proyek dan orang-orang yang menciptakannya! --- ## Pedagogi -Kami memilih dua prinsip pedagogis saat membangun kurikulum ini: memastikan bahwa itu berbasis **proyek langsung** dan mencakup **kuis yang sering**. Selain itu, kurikulum ini memiliki **tema** umum agar lebih terpadu. +Kami memilih dua prinsip pedagogis saat membangun kurikulum ini: memastikan bahwa kurikulum ini berbasis **proyek yang praktis** dan menyertakan **kuis yang sering**. Selain itu, kurikulum ini memiliki **tema** yang konsisten untuk memberikan kohesi. -Dengan memastikan isi selaras dengan proyek, proses menjadi lebih menarik bagi siswa dan memperkuat retensi konsep. Selain itu, kuis dengan tingkat tekanan rendah sebelum kelas mengarahkan niat siswa untuk mempelajari topik, sementara kuis kedua setelah kelas memastikan retensi lebih lanjut. Kurikulum ini dirancang agar fleksibel dan menyenangkan serta dapat diambil secara lengkap atau sebagian. Proyek dimulai dari yang sederhana dan menjadi semakin kompleks hingga akhir siklus 12 minggu. Kurikulum ini juga mencakup posskrip tentang aplikasi nyata ML, yang dapat digunakan sebagai nilai tambah atau sebagai dasar diskusi. +Dengan memastikan bahwa isi sejalan dengan proyek, proses belajar menjadi lebih menarik bagi siswa dan peningkatan retensi konsep akan terjadi. Selain itu, kuis ringan sebelum kelas menetapkan niat siswa untuk mempelajari topik, sementara kuis kedua setelah kelas memastikan retensi lebih lanjut. Kurikulum ini dirancang agar fleksibel dan menyenangkan, dan dapat diambil secara keseluruhan atau sebagian. Proyek dimulai dari yang kecil dan menjadi semakin kompleks pada akhir siklus 12 minggu. Kurikulum ini juga menyertakan catatan akhir tentang aplikasi nyata dari ML, yang dapat digunakan sebagai kredit tambahan atau sebagai dasar diskusi. -> Temukan [Kode Etik](CODE_OF_CONDUCT.md), [Kontribusi](CONTRIBUTING.md), [Terjemahan](TRANSLATIONS.md), dan pedoman [Pemecahan Masalah](TROUBLESHOOTING.md) kami. Kami menyambut umpan balik konstruktif Anda! +> Temukan [Kode Etik](CODE_OF_CONDUCT.md), [Kontribusi](CONTRIBUTING.md), [Terjemahan](TRANSLATIONS.md), dan [Pemecahan Masalah](TROUBLESHOOTING.md) kami. Kami menyambut umpan balik konstruktif Anda! -## Setiap pelajaran mencakup +## Setiap pelajaran meliputi - sketchnote opsional -- video pelengkap opsional -- video panduan (hanya beberapa pelajaran) -- [kuis pemanasan pra-kuliah](https://ff-quizzes.netlify.app/en/ml/) +- video tambahan opsional +- video walkthrough (hanya beberapa pelajaran) +- [kuis pemanasan pra-ceramah](https://ff-quizzes.netlify.app/en/ml/) - pelajaran tertulis - untuk pelajaran berbasis proyek, panduan langkah demi langkah cara membangun proyek -- pemeriksaan pengetahuan +- cek pengetahuan - tantangan -- bacaan pelengkap +- bacaan tambahan - tugas -- [kuis pasca-kuliah](https://ff-quizzes.netlify.app/en/ml/) - -> **Catatan tentang bahasa**: Pelajaran ini terutama ditulis dalam Python, tetapi banyak juga tersedia dalam R. Untuk menyelesaikan pelajaran R, buka folder `/solution` dan cari pelajaran R. Pelajaran tersebut memiliki ekstensi .rmd yang merupakan file **R Markdown** yang dapat didefinisikan sebagai gabungan `potongan kode` (dari R atau bahasa lain) dan `header YAML` (yang mengarahkan bagaimana memformat keluaran seperti PDF) dalam dokumen `Markdown`. Dengan demikian, ia berfungsi sebagai kerangka kerja pembuatan yang sangat baik untuk ilmu data karena memungkinkan Anda menggabungkan kode, outputnya, dan pemikiran Anda dengan menuliskannya dalam Markdown. Selain itu, dokumen R Markdown dapat dirender ke format keluaran seperti PDF, HTML, atau Word. -> **Catatan tentang kuis**: Semua kuis terdapat di dalam [folder Quiz App](../../quiz-app), dengan total 52 kuis yang masing-masing berisi tiga pertanyaan. Kuis tersebut ditautkan di dalam pelajaran, tetapi aplikasi kuis dapat dijalankan secara lokal; ikuti instruksi di folder `quiz-app` untuk menghosting secara lokal atau men-deploy ke Azure. - -| Nomor Pelajaran | Topik | Pengelompokan Pelajaran | Tujuan Pembelajaran | Pelajaran Tautan | Penulis | -| :--------------: | :------------------------------------------------------------: | :----------------------------------------------------------: | ------------------------------------------------------------------------------------------------------------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------: | -| 01 | Pengenalan machine learning | [Pengenalan](1-Introduction/README.md) | Pelajari konsep dasar di balik machine learning | [Pelajaran](1-Introduction/1-intro-to-ML/README.md) | Muhammad | -| 02 | Sejarah machine learning | [Pengenalan](1-Introduction/README.md) | Pelajari sejarah yang mendasari bidang ini | [Pelajaran](1-Introduction/2-history-of-ML/README.md) | Jen dan Amy | -| 03 | Keadilan dan machine learning | [Pengenalan](1-Introduction/README.md) | Apa isu filosofis penting tentang keadilan yang harus dipertimbangkan oleh siswa saat membangun dan menerapkan model ML? | [Pelajaran](1-Introduction/3-fairness/README.md) | Tomomi | -| 04 | Teknik untuk machine learning | [Pengenalan](1-Introduction/README.md) | Teknik apa yang digunakan peneliti ML untuk membangun model ML? | [Pelajaran](1-Introduction/4-techniques-of-ML/README.md) | Chris dan Jen | -| 05 | Pengenalan regresi | [Regresi](2-Regression/README.md) | Mulai dengan Python dan Scikit-learn untuk model regresi | [Python](2-Regression/1-Tools/README.md) • [R](../../2-Regression/1-Tools/solution/R/lesson_1.html) | Jen • Eric Wanjau | -| 06 | Harga labu Amerika Utara 🎃 | [Regresi](2-Regression/README.md) | Visualisasikan dan bersihkan data sebagai persiapan untuk ML | [Python](2-Regression/2-Data/README.md) • [R](../../2-Regression/2-Data/solution/R/lesson_2.html) | Jen • Eric Wanjau | -| 07 | Harga labu Amerika Utara 🎃 | [Regresi](2-Regression/README.md) | Bangun model regresi linier dan polinomial | [Python](2-Regression/3-Linear/README.md) • [R](../../2-Regression/3-Linear/solution/R/lesson_3.html) | Jen dan Dmitry • Eric Wanjau | -| 08 | Harga labu Amerika Utara 🎃 | [Regresi](2-Regression/README.md) | Bangun model regresi logistik | [Python](2-Regression/4-Logistic/README.md) • [R](../../2-Regression/4-Logistic/solution/R/lesson_4.html) | Jen • Eric Wanjau | -| 09 | Aplikasi Web 🔌 | [Aplikasi Web](3-Web-App/README.md) | Bangun aplikasi web untuk menggunakan model yang sudah dilatih | [Python](3-Web-App/1-Web-App/README.md) | Jen | -| 10 | Pengenalan klasifikasi | [Klasifikasi](4-Classification/README.md) | Bersihkan, persiapkan, dan visualisasikan data Anda; pengantar klasifikasi | [Python](4-Classification/1-Introduction/README.md) • [R](../../4-Classification/1-Introduction/solution/R/lesson_10.html) | Jen dan Cassie • Eric Wanjau | -| 11 | Masakan Asia dan India yang Lezat 🍜 | [Klasifikasi](4-Classification/README.md) | Pengenalan kepada pengklasifikasi | [Python](4-Classification/2-Classifiers-1/README.md) • [R](../../4-Classification/2-Classifiers-1/solution/R/lesson_11.html) | Jen dan Cassie • Eric Wanjau | -| 12 | Masakan Asia dan India yang Lezat 🍜 | [Klasifikasi](4-Classification/README.md) | Lebih banyak pengklasifikasi | [Python](4-Classification/3-Classifiers-2/README.md) • [R](../../4-Classification/3-Classifiers-2/solution/R/lesson_12.html) | Jen dan Cassie • Eric Wanjau | -| 13 | Masakan Asia dan India yang Lezat 🍜 | [Klasifikasi](4-Classification/README.md) | Bangun aplikasi rekomender web menggunakan model Anda | [Python](4-Classification/4-Applied/README.md) | Jen | -| 14 | Pengenalan klastering | [Klastering](5-Clustering/README.md) | Bersihkan, persiapkan, dan visualisasikan data Anda; pengantar klastering | [Python](5-Clustering/1-Visualize/README.md) • [R](../../5-Clustering/1-Visualize/solution/R/lesson_14.html) | Jen • Eric Wanjau | -| 15 | Menjelajahi Selera Musik Nigeria 🎧 | [Klastering](5-Clustering/README.md) | Jelajahi metode klastering K-Means | [Python](5-Clustering/2-K-Means/README.md) • [R](../../5-Clustering/2-K-Means/solution/R/lesson_15.html) | Jen • Eric Wanjau | -| 16 | Pengenalan pemrosesan bahasa alami ☕️ | [Pemrosesan bahasa alami](6-NLP/README.md) | Pelajari dasar-dasar NLP dengan membangun bot sederhana | [Python](6-NLP/1-Introduction-to-NLP/README.md) | Stephen | -| 17 | Tugas Umum NLP ☕️ | [Pemrosesan bahasa alami](6-NLP/README.md) | Perdalam pengetahuan NLP Anda dengan memahami tugas umum yang diperlukan saat menangani struktur bahasa | [Python](6-NLP/2-Tasks/README.md) | Stephen | -| 18 | Terjemahan dan analisis sentimen ♥️ | [Pemrosesan bahasa alami](6-NLP/README.md) | Terjemahan dan analisis sentimen dengan Jane Austen | [Python](6-NLP/3-Translation-Sentiment/README.md) | Stephen | -| 19 | Hotel romantis di Eropa ♥️ | [Pemrosesan bahasa alami](6-NLP/README.md) | Analisis sentimen dengan ulasan hotel 1 | [Python](6-NLP/4-Hotel-Reviews-1/README.md) | Stephen | -| 20 | Hotel romantis di Eropa ♥️ | [Pemrosesan bahasa alami](6-NLP/README.md) | Analisis sentimen dengan ulasan hotel 2 | [Python](6-NLP/5-Hotel-Reviews-2/README.md) | Stephen | -| 21 | Pengenalan peramalan deret waktu | [Deret waktu](7-TimeSeries/README.md) | Pengenalan kepada peramalan deret waktu | [Python](7-TimeSeries/1-Introduction/README.md) | Francesca | -| 22 | ⚡️ Penggunaan Listrik Dunia ⚡️ - peramalan deret waktu dengan ARIMA | [Deret waktu](7-TimeSeries/README.md) | Peramalan deret waktu dengan ARIMA | [Python](7-TimeSeries/2-ARIMA/README.md) | Francesca | -| 23 | ⚡️ Penggunaan Listrik Dunia ⚡️ - peramalan deret waktu dengan SVR | [Deret waktu](7-TimeSeries/README.md) | Peramalan deret waktu dengan Support Vector Regressor | [Python](7-TimeSeries/3-SVR/README.md) | Anirban | -| 24 | Pengenalan pembelajaran penguatan | [Pembelajaran penguatan](8-Reinforcement/README.md) | Pengenalan pembelajaran penguatan dengan Q-Learning | [Python](8-Reinforcement/1-QLearning/README.md) | Dmitry | -| 25 | Bantu Peter menghindari serigala! 🐺 | [Pembelajaran penguatan](8-Reinforcement/README.md) | Pembelajaran penguatan Gym | [Python](8-Reinforcement/2-Gym/README.md) | Dmitry | -| Postscript | Skenario dan aplikasi ML di dunia nyata | [ML di Dunia Nyata](9-Real-World/README.md) | Aplikasi ML klasik yang menarik dan mengungkap dalam dunia nyata | [Pelajaran](9-Real-World/1-Applications/README.md) | Tim | -| Postscript | Debugging Model dalam ML menggunakan dasbor RAI | [ML di Dunia Nyata](9-Real-World/README.md) | Debugging Model dalam Machine Learning menggunakan komponen dasbor Responsible AI | [Pelajaran](9-Real-World/2-Debugging-ML-Models/README.md) | Ruth Yakubu | - -> [temukan semua sumber tambahan untuk kursus ini dalam koleksi Microsoft Learn kami](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) - -## Akses offline - -Anda dapat menjalankan dokumentasi ini secara offline dengan menggunakan [Docsify](https://docsify.js.org/#/). Fork repo ini, [instal Docsify](https://docsify.js.org/#/quickstart) pada mesin lokal Anda, kemudian di folder root repo ini, ketik `docsify serve`. Situs web akan disajikan pada port 3000 di localhost Anda: `localhost:3000`. +- [kuis pasca-ceramah](https://ff-quizzes.netlify.app/en/ml/) + +> **Catatan tentang bahasa**: Pelajaran-pelajaran ini terutama ditulis dalam Python, tetapi banyak juga tersedia dalam R. Untuk menyelesaikan pelajaran R, buka folder `/solution` dan cari pelajaran R. Mereka menyertakan ekstensi .rmd yang mewakili file **R Markdown** yang dapat didefinisikan sebagai penyisipan `potongan kode` (dari R atau bahasa lain) dan `header YAML` (yang mengarahkan bagaimana memformat output seperti PDF) dalam `dokumen Markdown`. Dengan demikian, ini berfungsi sebagai kerangka kerja penulisan contoh untuk ilmu data karena memungkinkan Anda menggabungkan kode, hasilnya, dan pemikiran Anda dengan menuliskannya dalam Markdown. Selain itu, dokumen R Markdown dapat dirender ke format output seperti PDF, HTML, atau Word. +> **Catatan tentang kuis**: Semua kuis terdapat dalam [folder Quiz App](../../quiz-app), dengan total 52 kuis yang masing-masing terdiri dari tiga pertanyaan. Kuis tersebut terhubung dari dalam pelajaran tetapi aplikasi kuis dapat dijalankan secara lokal; ikuti instruksi di folder `quiz-app` untuk meng-host secara lokal atau deploy ke Azure. + +| Nomor Pelajaran | Topik | Kelompok Pelajaran | Tujuan Pembelajaran | Pelajaran Terkait | Penulis | +| :--------------: | :------------------------------------------------------------: | :----------------------------------------------------: | ------------------------------------------------------------------------------------------------------------------------------- | :-----------------------------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------: | +| 01 | Pengenalan pembelajaran mesin | [Pengenalan](1-Introduction/README.md) | Pelajari konsep dasar di balik pembelajaran mesin | [Pelajaran](1-Introduction/1-intro-to-ML/README.md) | Muhammad | +| 02 | Sejarah pembelajaran mesin | [Pengenalan](1-Introduction/README.md) | Pelajari sejarah yang mendasari bidang ini | [Pelajaran](1-Introduction/2-history-of-ML/README.md) | Jen dan Amy | +| 03 | Keadilan dan pembelajaran mesin | [Pengenalan](1-Introduction/README.md) | Apa saja isu filosofis penting tentang keadilan yang harus dipertimbangkan siswa saat membangun dan menerapkan model ML? | [Pelajaran](1-Introduction/3-fairness/README.md) | Tomomi | +| 04 | Teknik untuk pembelajaran mesin | [Pengenalan](1-Introduction/README.md) | Teknik apa yang digunakan para peneliti ML untuk membangun model ML? | [Pelajaran](1-Introduction/4-techniques-of-ML/README.md) | Chris dan Jen | +| 05 | Pengenalan regresi | [Regresi](2-Regression/README.md) | Mulai dengan Python dan Scikit-learn untuk model regresi | [Python](2-Regression/1-Tools/README.md) • [R](../../2-Regression/1-Tools/solution/R/lesson_1.html) | Jen • Eric Wanjau | +| 06 | Harga labu Amerika Utara 🎃 | [Regresi](2-Regression/README.md) | Visualisasikan dan bersihkan data sebagai persiapan untuk ML | [Python](2-Regression/2-Data/README.md) • [R](../../2-Regression/2-Data/solution/R/lesson_2.html) | Jen • Eric Wanjau | +| 07 | Harga labu Amerika Utara 🎃 | [Regresi](2-Regression/README.md) | Bangun model regresi linier dan polinomial | [Python](2-Regression/3-Linear/README.md) • [R](../../2-Regression/3-Linear/solution/R/lesson_3.html) | Jen dan Dmitry • Eric Wanjau | +| 08 | Harga labu Amerika Utara 🎃 | [Regresi](2-Regression/README.md) | Bangun model regresi logistik | [Python](2-Regression/4-Logistic/README.md) • [R](../../2-Regression/4-Logistic/solution/R/lesson_4.html) | Jen • Eric Wanjau | +| 09 | Aplikasi Web 🔌 | [Aplikasi Web](3-Web-App/README.md) | Bangun aplikasi web untuk menggunakan model yang Anda latih | [Python](3-Web-App/1-Web-App/README.md) | Jen | +| 10 | Pengenalan klasifikasi | [Klasifikasi](4-Classification/README.md) | Bersihkan, persiapkan, dan visualisasikan data Anda; pengenalan klasifikasi | [Python](4-Classification/1-Introduction/README.md) • [R](../../4-Classification/1-Introduction/solution/R/lesson_10.html) | Jen dan Cassie • Eric Wanjau | +| 11 | Masakan Asia dan India yang lezat 🍜 | [Klasifikasi](4-Classification/README.md) | Pengenalan klasifikator | [Python](4-Classification/2-Classifiers-1/README.md) • [R](../../4-Classification/2-Classifiers-1/solution/R/lesson_11.html) | Jen dan Cassie • Eric Wanjau | +| 12 | Masakan Asia dan India yang lezat 🍜 | [Klasifikasi](4-Classification/README.md) | Lebih banyak klasifikator | [Python](4-Classification/3-Classifiers-2/README.md) • [R](../../4-Classification/3-Classifiers-2/solution/R/lesson_12.html) | Jen dan Cassie • Eric Wanjau | +| 13 | Masakan Asia dan India yang lezat 🍜 | [Klasifikasi](4-Classification/README.md) | Bangun aplikasi web rekomendasi menggunakan model Anda | [Python](4-Classification/4-Applied/README.md) | Jen | +| 14 | Pengenalan klastering | [Klastering](5-Clustering/README.md) | Bersihkan, persiapkan, dan visualisasikan data Anda; pengenalan klastering | [Python](5-Clustering/1-Visualize/README.md) • [R](../../5-Clustering/1-Visualize/solution/R/lesson_14.html) | Jen • Eric Wanjau | +| 15 | Menjelajahi selera musik Nigeria 🎧 | [Klastering](5-Clustering/README.md) | Jelajahi metode klastering K-Means | [Python](5-Clustering/2-K-Means/README.md) • [R](../../5-Clustering/2-K-Means/solution/R/lesson_15.html) | Jen • Eric Wanjau | +| 16 | Pengenalan pemrosesan bahasa alami ☕️ | [Pemrosesan bahasa alami](6-NLP/README.md) | Pelajari dasar-dasar NLP dengan membangun bot sederhana | [Python](6-NLP/1-Introduction-to-NLP/README.md) | Stephen | +| 17 | Tugas NLP Umum ☕️ | [Pemrosesan bahasa alami](6-NLP/README.md) | Perdalam pengetahuan NLP Anda dengan memahami tugas umum yang diperlukan saat berhadapan dengan struktur bahasa | [Python](6-NLP/2-Tasks/README.md) | Stephen | +| 18 | Terjemahan dan analisis sentimen ♥️ | [Pemrosesan bahasa alami](6-NLP/README.md) | Terjemahan dan analisis sentimen dengan Jane Austen | [Python](6-NLP/3-Translation-Sentiment/README.md) | Stephen | +| 19 | Hotel romantis di Eropa ♥️ | [Pemrosesan bahasa alami](6-NLP/README.md) | Analisis sentimen dengan ulasan hotel 1 | [Python](6-NLP/4-Hotel-Reviews-1/README.md) | Stephen | +| 20 | Hotel romantis di Eropa ♥️ | [Pemrosesan bahasa alami](6-NLP/README.md) | Analisis sentimen dengan ulasan hotel 2 | [Python](6-NLP/5-Hotel-Reviews-2/README.md) | Stephen | +| 21 | Pengenalan peramalan deret waktu | [Deret waktu](7-TimeSeries/README.md) | Pengenalan peramalan deret waktu | [Python](7-TimeSeries/1-Introduction/README.md) | Francesca | +| 22 | ⚡️ Penggunaan Daya Dunia ⚡️ - peramalan deret waktu dengan ARIMA | [Deret waktu](7-TimeSeries/README.md) | Peramalan deret waktu dengan ARIMA | [Python](7-TimeSeries/2-ARIMA/README.md) | Francesca | +| 23 | ⚡️ Penggunaan Daya Dunia ⚡️ - peramalan deret waktu dengan SVR | [Deret waktu](7-TimeSeries/README.md) | Peramalan deret waktu dengan Support Vector Regressor | [Python](7-TimeSeries/3-SVR/README.md) | Anirban | +| 24 | Pengenalan pembelajaran penguatan | [Pembelajaran penguatan](8-Reinforcement/README.md) | Pengenalan pembelajaran penguatan dengan Q-Learning | [Python](8-Reinforcement/1-QLearning/README.md) | Dmitry | +| 25 | Bantu Peter menghindari serigala! 🐺 | [Pembelajaran penguatan](8-Reinforcement/README.md) | Gym pembelajaran penguatan | [Python](8-Reinforcement/2-Gym/README.md) | Dmitry | +| Catatan | Skenario dan aplikasi ML dunia nyata | [ML di Dunia Nyata](9-Real-World/README.md) | Aplikasi nyata yang menarik dan mengungkap dari ML klasik | [Pelajaran](9-Real-World/1-Applications/README.md) | Tim | +| Catatan | Debugging Model dalam ML menggunakan dashboard RAI | [ML di Dunia Nyata](9-Real-World/README.md) | Debugging Model dalam Pembelajaran Mesin menggunakan komponen dashboard Responsible AI | [Pelajaran](9-Real-World/2-Debugging-ML-Models/README.md) | Ruth Yakubu | + +> [temukan semua sumber tambahan untuk kursus ini di koleksi Microsoft Learn kami](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) + +## Akses Offline + +Anda dapat menjalankan dokumentasi ini secara offline dengan menggunakan [Docsify](https://docsify.js.org/#/). Fork repo ini, [pasang Docsify](https://docsify.js.org/#/quickstart) di mesin lokal Anda, lalu di folder root repo ini, ketik `docsify serve`. Website akan disajikan pada port 3000 di localhost Anda: `localhost:3000`. ## PDF Temukan pdf kurikulum dengan tautan [di sini](https://microsoft.github.io/ML-For-Beginners/pdf/readme.pdf). + ## 🎒 Kursus Lainnya -Tim kami memproduksi kursus lainnya! Cek: +Tim kami juga menghasilkan kursus lain! Cek: ### LangChain -[![LangChain4j untuk Pemula](https://img.shields.io/badge/LangChain4j%20for%20Beginners-22C55E?style=for-the-badge&&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchain4j-for-beginners) -[![LangChain.js untuk Pemula](https://img.shields.io/badge/LangChain.js%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchainjs-for-beginners?WT.mc_id=m365-94501-dwahlin) +[![LangChain4j for Beginners](https://img.shields.io/badge/LangChain4j%20for%20Beginners-22C55E?style=for-the-badge&&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchain4j-for-beginners) +[![LangChain.js for Beginners](https://img.shields.io/badge/LangChain.js%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchainjs-for-beginners?WT.mc_id=m365-94501-dwahlin) --- ### Azure / Edge / MCP / Agen -[![AZD untuk Pemula](https://img.shields.io/badge/AZD%20for%20Beginners-0078D4?style=for-the-badge&labelColor=E5E7EB&color=0078D4)](https://github.com/microsoft/AZD-for-beginners?WT.mc_id=academic-105485-koreyst) -[![Edge AI untuk Pemula](https://img.shields.io/badge/Edge%20AI%20for%20Beginners-00B8E4?style=for-the-badge&labelColor=E5E7EB&color=00B8E4)](https://github.com/microsoft/edgeai-for-beginners?WT.mc_id=academic-105485-koreyst) -[![MCP untuk Pemula](https://img.shields.io/badge/MCP%20for%20Beginners-009688?style=for-the-badge&labelColor=E5E7EB&color=009688)](https://github.com/microsoft/mcp-for-beginners?WT.mc_id=academic-105485-koreyst) -[![Agen AI untuk Pemula](https://img.shields.io/badge/AI%20Agents%20for%20Beginners-00C49A?style=for-the-badge&labelColor=E5E7EB&color=00C49A)](https://github.com/microsoft/ai-agents-for-beginners?WT.mc_id=academic-105485-koreyst) +[![AZD for Beginners](https://img.shields.io/badge/AZD%20for%20Beginners-0078D4?style=for-the-badge&labelColor=E5E7EB&color=0078D4)](https://github.com/microsoft/AZD-for-beginners?WT.mc_id=academic-105485-koreyst) +[![Edge AI for Beginners](https://img.shields.io/badge/Edge%20AI%20for%20Beginners-00B8E4?style=for-the-badge&labelColor=E5E7EB&color=00B8E4)](https://github.com/microsoft/edgeai-for-beginners?WT.mc_id=academic-105485-koreyst) +[![MCP for Beginners](https://img.shields.io/badge/MCP%20for%20Beginners-009688?style=for-the-badge&labelColor=E5E7EB&color=009688)](https://github.com/microsoft/mcp-for-beginners?WT.mc_id=academic-105485-koreyst) +[![AI Agents for Beginners](https://img.shields.io/badge/AI%20Agents%20for%20Beginners-00C49A?style=for-the-badge&labelColor=E5E7EB&color=00C49A)](https://github.com/microsoft/ai-agents-for-beginners?WT.mc_id=academic-105485-koreyst) --- - -### Seri AI Generatif -[![Generative AI for Beginners](https://img.shields.io/badge/Generative%20AI%20for%20Beginners-8B5CF6?style=for-the-badge&labelColor=E5E7EB&color=8B5CF6)](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-105485-koreyst) + +### Seri Generatif AI +[![Generative AI untuk Pemula](https://img.shields.io/badge/Generative%20AI%20for%20Beginners-8B5CF6?style=for-the-badge&labelColor=E5E7EB&color=8B5CF6)](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-105485-koreyst) [![Generative AI (.NET)](https://img.shields.io/badge/Generative%20AI%20(.NET)-9333EA?style=for-the-badge&labelColor=E5E7EB&color=9333EA)](https://github.com/microsoft/Generative-AI-for-beginners-dotnet?WT.mc_id=academic-105485-koreyst) [![Generative AI (Java)](https://img.shields.io/badge/Generative%20AI%20(Java)-C084FC?style=for-the-badge&labelColor=E5E7EB&color=C084FC)](https://github.com/microsoft/generative-ai-for-beginners-java?WT.mc_id=academic-105485-koreyst) [![Generative AI (JavaScript)](https://img.shields.io/badge/Generative%20AI%20(JavaScript)-E879F9?style=for-the-badge&labelColor=E5E7EB&color=E879F9)](https://github.com/microsoft/generative-ai-with-javascript?WT.mc_id=academic-105485-koreyst) @@ -197,29 +189,29 @@ Tim kami memproduksi kursus lainnya! Cek: --- ### Pembelajaran Inti -[![ML for Beginners](https://img.shields.io/badge/ML%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=22C55E)](https://aka.ms/ml-beginners?WT.mc_id=academic-105485-koreyst) -[![Data Science for Beginners](https://img.shields.io/badge/Data%20Science%20for%20Beginners-84CC16?style=for-the-badge&labelColor=E5E7EB&color=84CC16)](https://aka.ms/datascience-beginners?WT.mc_id=academic-105485-koreyst) -[![AI for Beginners](https://img.shields.io/badge/AI%20for%20Beginners-A3E635?style=for-the-badge&labelColor=E5E7EB&color=A3E635)](https://aka.ms/ai-beginners?WT.mc_id=academic-105485-koreyst) -[![Cybersecurity for Beginners](https://img.shields.io/badge/Cybersecurity%20for%20Beginners-F97316?style=for-the-badge&labelColor=E5E7EB&color=F97316)](https://github.com/microsoft/Security-101?WT.mc_id=academic-96948-sayoung) -[![Web Dev for Beginners](https://img.shields.io/badge/Web%20Dev%20for%20Beginners-EC4899?style=for-the-badge&labelColor=E5E7EB&color=EC4899)](https://aka.ms/webdev-beginners?WT.mc_id=academic-105485-koreyst) -[![IoT for Beginners](https://img.shields.io/badge/IoT%20for%20Beginners-14B8A6?style=for-the-badge&labelColor=E5E7EB&color=14B8A6)](https://aka.ms/iot-beginners?WT.mc_id=academic-105485-koreyst) -[![XR Development for Beginners](https://img.shields.io/badge/XR%20Development%20for%20Beginners-38BDF8?style=for-the-badge&labelColor=E5E7EB&color=38BDF8)](https://github.com/microsoft/xr-development-for-beginners?WT.mc_id=academic-105485-koreyst) +[![ML untuk Pemula](https://img.shields.io/badge/ML%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=22C55E)](https://aka.ms/ml-beginners?WT.mc_id=academic-105485-koreyst) +[![Data Science untuk Pemula](https://img.shields.io/badge/Data%20Science%20for%20Beginners-84CC16?style=for-the-badge&labelColor=E5E7EB&color=84CC16)](https://aka.ms/datascience-beginners?WT.mc_id=academic-105485-koreyst) +[![AI untuk Pemula](https://img.shields.io/badge/AI%20for%20Beginners-A3E635?style=for-the-badge&labelColor=E5E7EB&color=A3E635)](https://aka.ms/ai-beginners?WT.mc_id=academic-105485-koreyst) +[![Keamanan Siber untuk Pemula](https://img.shields.io/badge/Cybersecurity%20for%20Beginners-F97316?style=for-the-badge&labelColor=E5E7EB&color=F97316)](https://github.com/microsoft/Security-101?WT.mc_id=academic-96948-sayoung) +[![Pengembangan Web untuk Pemula](https://img.shields.io/badge/Web%20Dev%20for%20Beginners-EC4899?style=for-the-badge&labelColor=E5E7EB&color=EC4899)](https://aka.ms/webdev-beginners?WT.mc_id=academic-105485-koreyst) +[![IoT untuk Pemula](https://img.shields.io/badge/IoT%20for%20Beginners-14B8A6?style=for-the-badge&labelColor=E5E7EB&color=14B8A6)](https://aka.ms/iot-beginners?WT.mc_id=academic-105485-koreyst) +[![Pengembangan XR untuk Pemula](https://img.shields.io/badge/XR%20Development%20for%20Beginners-38BDF8?style=for-the-badge&labelColor=E5E7EB&color=38BDF8)](https://github.com/microsoft/xr-development-for-beginners?WT.mc_id=academic-105485-koreyst) --- ### Seri Copilot -[![Copilot for AI Paired Programming](https://img.shields.io/badge/Copilot%20for%20AI%20Paired%20Programming-FACC15?style=for-the-badge&labelColor=E5E7EB&color=FACC15)](https://aka.ms/GitHubCopilotAI?WT.mc_id=academic-105485-koreyst) -[![Copilot for C#/.NET](https://img.shields.io/badge/Copilot%20for%20C%23/.NET-FBBF24?style=for-the-badge&labelColor=E5E7EB&color=FBBF24)](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers?WT.mc_id=academic-105485-koreyst) -[![Copilot Adventure](https://img.shields.io/badge/Copilot%20Adventure-FDE68A?style=for-the-badge&labelColor=E5E7EB&color=FDE68A)](https://github.com/microsoft/CopilotAdventures?WT.mc_id=academic-105485-koreyst) +[![Copilot untuk Pemrograman Berpasangan AI](https://img.shields.io/badge/Copilot%20for%20AI%20Paired%20Programming-FACC15?style=for-the-badge&labelColor=E5E7EB&color=FACC15)](https://aka.ms/GitHubCopilotAI?WT.mc_id=academic-105485-koreyst) +[![Copilot untuk C#/.NET](https://img.shields.io/badge/Copilot%20for%20C%23/.NET-FBBF24?style=for-the-badge&labelColor=E5E7EB&color=FBBF24)](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers?WT.mc_id=academic-105485-koreyst) +[![Petualangan Copilot](https://img.shields.io/badge/Copilot%20Adventure-FDE68A?style=for-the-badge&labelColor=E5E7EB&color=FDE68A)](https://github.com/microsoft/CopilotAdventures?WT.mc_id=academic-105485-koreyst) ## Mendapatkan Bantuan -Jika Anda mengalami kebuntuan atau memiliki pertanyaan tentang membangun aplikasi AI. Bergabunglah dengan sesama pelajar dan pengembang berpengalaman dalam diskusi tentang MCP. Ini adalah komunitas yang suportif di mana pertanyaan disambut dan pengetahuan dibagikan dengan bebas. +Jika Anda mengalami kesulitan atau memiliki pertanyaan tentang membangun aplikasi AI. Bergabunglah dengan sesama pelajar dan pengembang berpengalaman dalam diskusi tentang MCP. Ini adalah komunitas yang mendukung di mana pertanyaan disambut dan pengetahuan dibagikan secara bebas. [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -Jika Anda memiliki umpan balik produk atau menemui kesalahan saat membangun, kunjungi: +Jika Anda memiliki masukan produk atau menemukan kesalahan saat membangun kunjungi: [![Microsoft Foundry Developer Forum](https://img.shields.io/badge/GitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https://aka.ms/foundry/forum) @@ -227,5 +219,5 @@ Jika Anda memiliki umpan balik produk atau menemui kesalahan saat membangun, kun **Penafian**: -Dokumen ini telah diterjemahkan menggunakan layanan terjemahan AI [Co-op Translator](https://github.com/Azure/co-op-translator). Meskipun kami berupaya untuk akurasi, harap diketahui bahwa terjemahan otomatis mungkin mengandung kesalahan atau ketidakakuratan. Dokumen asli dalam bahasa aslinya harus dianggap sebagai sumber yang sahih. Untuk informasi penting, disarankan menggunakan terjemahan profesional oleh manusia. Kami tidak bertanggung jawab atas kesalahpahaman atau penafsiran yang salah yang timbul dari penggunaan terjemahan ini. +Dokumen ini telah diterjemahkan menggunakan layanan terjemahan AI [Co-op Translator](https://github.com/Azure/co-op-translator). Meskipun kami berupaya menjaga keakuratan, harap diketahui bahwa terjemahan otomatis mungkin mengandung kesalahan atau ketidakakuratan. Dokumen asli dalam bahasa aslinya harus dianggap sebagai sumber yang sah. Untuk informasi yang penting, disarankan menggunakan jasa penerjemahan profesional oleh manusia. Kami tidak bertanggung jawab atas kesalahpahaman atau kesalahan tafsir yang timbul dari penggunaan terjemahan ini. \ No newline at end of file diff --git a/translations/id/SECURITY.md b/translations/id/SECURITY.md index 6ab647656..a861fc5f9 100644 --- a/translations/id/SECURITY.md +++ b/translations/id/SECURITY.md @@ -1,12 +1,3 @@ - ## Keamanan Microsoft sangat memperhatikan keamanan produk dan layanan perangkat lunaknya, termasuk semua repositori kode sumber yang dikelola melalui organisasi GitHub kami, yang mencakup [Microsoft](https://github.com/Microsoft), [Azure](https://github.com/Azure), [DotNet](https://github.com/dotnet), [AspNet](https://github.com/aspnet), [Xamarin](https://github.com/xamarin), dan [organisasi GitHub kami](https://opensource.microsoft.com/). diff --git a/translations/id/SUPPORT.md b/translations/id/SUPPORT.md index b9f756c89..c9ae4cf72 100644 --- a/translations/id/SUPPORT.md +++ b/translations/id/SUPPORT.md @@ -1,12 +1,3 @@ - # Dukungan ## Cara Melaporkan Masalah dan Mendapatkan Bantuan diff --git a/translations/id/TROUBLESHOOTING.md b/translations/id/TROUBLESHOOTING.md index 279a016a2..26e5faa96 100644 --- a/translations/id/TROUBLESHOOTING.md +++ b/translations/id/TROUBLESHOOTING.md @@ -1,12 +1,3 @@ - # Panduan Pemecahan Masalah Panduan ini membantu Anda menyelesaikan masalah umum saat bekerja dengan kurikulum Machine Learning untuk Pemula. Jika Anda tidak menemukan solusi di sini, silakan cek [Diskusi Discord](https://aka.ms/foundry/discord) atau [buka masalah baru](https://github.com/microsoft/ML-For-Beginners/issues). diff --git a/translations/id/docs/_sidebar.md b/translations/id/docs/_sidebar.md index 50f64cf4f..7fd40876e 100644 --- a/translations/id/docs/_sidebar.md +++ b/translations/id/docs/_sidebar.md @@ -1,12 +1,3 @@ - - Pendahuluan - [Pendahuluan tentang Machine Learning](../1-Introduction/1-intro-to-ML/README.md) - [Sejarah Machine Learning](../1-Introduction/2-history-of-ML/README.md) diff --git a/translations/id/for-teachers.md b/translations/id/for-teachers.md index 2d428370c..b03ecebb8 100644 --- a/translations/id/for-teachers.md +++ b/translations/id/for-teachers.md @@ -1,12 +1,3 @@ - ## Untuk Pendidik Apakah Anda ingin menggunakan kurikulum ini di kelas Anda? Silakan saja! diff --git a/translations/id/quiz-app/README.md b/translations/id/quiz-app/README.md index 2a822b910..6307f0b53 100644 --- a/translations/id/quiz-app/README.md +++ b/translations/id/quiz-app/README.md @@ -1,12 +1,3 @@ - # Kuis Kuis ini adalah kuis sebelum dan sesudah kuliah untuk kurikulum ML di https://aka.ms/ml-beginners diff --git a/translations/id/sketchnotes/LICENSE.md b/translations/id/sketchnotes/LICENSE.md index 00acf7d25..3b270ca67 100644 --- a/translations/id/sketchnotes/LICENSE.md +++ b/translations/id/sketchnotes/LICENSE.md @@ -1,12 +1,3 @@ - Hak Atribusi-BerbagiSerupa 4.0 Internasional ======================================================================= diff --git a/translations/id/sketchnotes/README.md b/translations/id/sketchnotes/README.md index a422eedd5..397355ba6 100644 --- a/translations/id/sketchnotes/README.md +++ b/translations/id/sketchnotes/README.md @@ -1,12 +1,3 @@ - Semua sketchnote kurikulum dapat diunduh di sini. 🖨 Untuk mencetak dalam resolusi tinggi, versi TIFF tersedia di [repo ini](https://github.com/girliemac/a-picture-is-worth-a-1000-words/tree/main/ml/tiff). diff --git a/translations/ms/.co-op-translator.json b/translations/ms/.co-op-translator.json new file mode 100644 index 000000000..7a531c63d --- /dev/null +++ b/translations/ms/.co-op-translator.json @@ -0,0 +1,596 @@ +{ + "1-Introduction/1-intro-to-ML/README.md": { + "original_hash": "69389392fa6346e0dfa30f664b7b6fec", + "translation_date": "2025-09-05T19:39:56+00:00", + "source_file": "1-Introduction/1-intro-to-ML/README.md", + "language_code": "ms" + }, + "1-Introduction/1-intro-to-ML/assignment.md": { + "original_hash": "4c4698044bb8af52cfb6388a4ee0e53b", + "translation_date": "2025-09-05T19:40:45+00:00", + "source_file": "1-Introduction/1-intro-to-ML/assignment.md", + "language_code": "ms" + }, + "1-Introduction/2-history-of-ML/README.md": { + "original_hash": "6a05fec147e734c3e6bfa54505648e2b", + "translation_date": "2025-09-05T19:43:05+00:00", + 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b/translations/ms/1-Introduction/1-intro-to-ML/README.md index 9bc4f5c50..46e0f20f5 100644 --- a/translations/ms/1-Introduction/1-intro-to-ML/README.md +++ b/translations/ms/1-Introduction/1-intro-to-ML/README.md @@ -1,12 +1,3 @@ - # Pengenalan kepada pembelajaran mesin ## [Kuiz sebelum kuliah](https://ff-quizzes.netlify.app/en/ml/) diff --git a/translations/ms/1-Introduction/1-intro-to-ML/assignment.md b/translations/ms/1-Introduction/1-intro-to-ML/assignment.md index 4671bf4ca..4e9614f42 100644 --- a/translations/ms/1-Introduction/1-intro-to-ML/assignment.md +++ b/translations/ms/1-Introduction/1-intro-to-ML/assignment.md @@ -1,12 +1,3 @@ - # Mula dan Beroperasi ## Arahan diff --git a/translations/ms/1-Introduction/2-history-of-ML/README.md b/translations/ms/1-Introduction/2-history-of-ML/README.md index ab7118815..0ceb57220 100644 --- a/translations/ms/1-Introduction/2-history-of-ML/README.md +++ b/translations/ms/1-Introduction/2-history-of-ML/README.md @@ -1,12 +1,3 @@ - # Sejarah pembelajaran mesin ![Ringkasan Sejarah pembelajaran mesin dalam sketchnote](../../../../sketchnotes/ml-history.png) diff --git a/translations/ms/1-Introduction/2-history-of-ML/assignment.md b/translations/ms/1-Introduction/2-history-of-ML/assignment.md index eb4d570cf..4dd8677e1 100644 --- a/translations/ms/1-Introduction/2-history-of-ML/assignment.md +++ b/translations/ms/1-Introduction/2-history-of-ML/assignment.md @@ -1,12 +1,3 @@ - # Buat Garis Masa ## Arahan diff --git a/translations/ms/1-Introduction/3-fairness/README.md b/translations/ms/1-Introduction/3-fairness/README.md index eadb46ff8..9e16d0341 100644 --- a/translations/ms/1-Introduction/3-fairness/README.md +++ b/translations/ms/1-Introduction/3-fairness/README.md @@ -1,12 +1,3 @@ - # Membina Penyelesaian Pembelajaran Mesin dengan AI yang Bertanggungjawab ![Ringkasan AI yang bertanggungjawab dalam Pembelajaran Mesin dalam bentuk sketchnote](../../../../sketchnotes/ml-fairness.png) diff --git a/translations/ms/1-Introduction/3-fairness/assignment.md b/translations/ms/1-Introduction/3-fairness/assignment.md index a802c8ac7..c70bdbdeb 100644 --- a/translations/ms/1-Introduction/3-fairness/assignment.md +++ b/translations/ms/1-Introduction/3-fairness/assignment.md @@ -1,12 +1,3 @@ - # Terokai Alat AI Bertanggungjawab ## Arahan diff --git a/translations/ms/1-Introduction/4-techniques-of-ML/README.md b/translations/ms/1-Introduction/4-techniques-of-ML/README.md index a4e7efa78..3f39f7c84 100644 --- a/translations/ms/1-Introduction/4-techniques-of-ML/README.md +++ b/translations/ms/1-Introduction/4-techniques-of-ML/README.md @@ -1,12 +1,3 @@ - # Teknik Pembelajaran Mesin Proses membina, menggunakan, dan mengekalkan model pembelajaran mesin serta data yang digunakan adalah sangat berbeza daripada banyak aliran kerja pembangunan lain. Dalam pelajaran ini, kita akan menjelaskan proses tersebut dan menggariskan teknik utama yang perlu anda ketahui. Anda akan: diff --git a/translations/ms/1-Introduction/4-techniques-of-ML/assignment.md b/translations/ms/1-Introduction/4-techniques-of-ML/assignment.md index 411dfbd6a..5e6fe1bd0 100644 --- a/translations/ms/1-Introduction/4-techniques-of-ML/assignment.md +++ b/translations/ms/1-Introduction/4-techniques-of-ML/assignment.md @@ -1,12 +1,3 @@ - # Temu bual seorang saintis data ## Arahan diff --git a/translations/ms/1-Introduction/README.md b/translations/ms/1-Introduction/README.md index 5986860a0..9ddd1d2dc 100644 --- a/translations/ms/1-Introduction/README.md +++ b/translations/ms/1-Introduction/README.md @@ -1,12 +1,3 @@ - # Pengenalan kepada pembelajaran mesin Dalam bahagian kurikulum ini, anda akan diperkenalkan kepada konsep asas yang mendasari bidang pembelajaran mesin, apa itu pembelajaran mesin, serta mempelajari sejarahnya dan teknik yang digunakan oleh para penyelidik untuk bekerja dengannya. Mari kita terokai dunia baru ML ini bersama-sama! diff --git a/translations/ms/2-Regression/1-Tools/README.md b/translations/ms/2-Regression/1-Tools/README.md index 253e83c24..9beb873c6 100644 --- a/translations/ms/2-Regression/1-Tools/README.md +++ b/translations/ms/2-Regression/1-Tools/README.md @@ -1,12 +1,3 @@ - # Bermula dengan Python dan Scikit-learn untuk model regresi ![Ringkasan regresi dalam sketchnote](../../../../sketchnotes/ml-regression.png) diff --git a/translations/ms/2-Regression/1-Tools/assignment.md b/translations/ms/2-Regression/1-Tools/assignment.md index 3ace92d09..4b8bb3cad 100644 --- a/translations/ms/2-Regression/1-Tools/assignment.md +++ b/translations/ms/2-Regression/1-Tools/assignment.md @@ -1,12 +1,3 @@ - # Regresi dengan Scikit-learn ## Arahan diff --git a/translations/ms/2-Regression/1-Tools/solution/Julia/README.md b/translations/ms/2-Regression/1-Tools/solution/Julia/README.md index 4a663c776..5da5c85e5 100644 --- a/translations/ms/2-Regression/1-Tools/solution/Julia/README.md +++ b/translations/ms/2-Regression/1-Tools/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/ms/2-Regression/2-Data/README.md b/translations/ms/2-Regression/2-Data/README.md index 3ec9c3d56..178df9263 100644 --- a/translations/ms/2-Regression/2-Data/README.md +++ b/translations/ms/2-Regression/2-Data/README.md @@ -1,12 +1,3 @@ - # Bina model regresi menggunakan Scikit-learn: sediakan dan visualisasikan data ![Infografik visualisasi data](../../../../2-Regression/2-Data/images/data-visualization.png) diff --git a/translations/ms/2-Regression/2-Data/assignment.md b/translations/ms/2-Regression/2-Data/assignment.md index d60d7a4bf..173ca704c 100644 --- a/translations/ms/2-Regression/2-Data/assignment.md +++ b/translations/ms/2-Regression/2-Data/assignment.md @@ -1,12 +1,3 @@ - # Meneroka Visualisasi Terdapat beberapa perpustakaan yang tersedia untuk visualisasi data. Cipta beberapa visualisasi menggunakan data Labu dalam pelajaran ini dengan matplotlib dan seaborn dalam buku nota sampel. Perpustakaan mana yang lebih mudah digunakan? diff --git a/translations/ms/2-Regression/2-Data/solution/Julia/README.md b/translations/ms/2-Regression/2-Data/solution/Julia/README.md index c633e9c6b..5da5c85e5 100644 --- a/translations/ms/2-Regression/2-Data/solution/Julia/README.md +++ b/translations/ms/2-Regression/2-Data/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/ms/2-Regression/3-Linear/README.md b/translations/ms/2-Regression/3-Linear/README.md index 4dacbd903..06e6ea4b1 100644 --- a/translations/ms/2-Regression/3-Linear/README.md +++ b/translations/ms/2-Regression/3-Linear/README.md @@ -1,12 +1,3 @@ - # Bina model regresi menggunakan Scikit-learn: empat cara regresi ![Infografik regresi linear vs polinomial](../../../../2-Regression/3-Linear/images/linear-polynomial.png) @@ -114,11 +105,11 @@ Sekarang setelah anda memahami matematik di sebalik regresi linear, mari kita bu Daripada pelajaran sebelumnya, anda mungkin telah melihat bahawa harga purata untuk bulan-bulan yang berbeza kelihatan seperti ini: -Harga purata mengikut bulan +Harga purata mengikut bulan Ini menunjukkan bahawa mungkin terdapat beberapa korelasi, dan kita boleh mencuba melatih model regresi linear untuk meramalkan hubungan antara `Bulan` dan `Harga`, atau antara `HariDalamTahun` dan `Harga`. Berikut adalah plot penyebaran yang menunjukkan hubungan yang terakhir: -Plot penyebaran Harga vs. Hari dalam Tahun +Plot penyebaran Harga vs. Hari dalam Tahun Mari kita lihat sama ada terdapat korelasi menggunakan fungsi `corr`: @@ -137,7 +128,7 @@ for i,var in enumerate(new_pumpkins['Variety'].unique()): ax = df.plot.scatter('DayOfYear','Price',ax=ax,c=colors[i],label=var) ``` -Plot penyebaran Harga vs. Hari dalam Tahun +Plot penyebaran Harga vs. Hari dalam Tahun Penyelidikan kita menunjukkan bahawa jenis labu mempunyai lebih banyak kesan terhadap harga keseluruhan daripada tarikh jualan sebenar. Kita boleh melihat ini dengan graf bar: @@ -145,7 +136,7 @@ Penyelidikan kita menunjukkan bahawa jenis labu mempunyai lebih banyak kesan ter new_pumpkins.groupby('Variety')['Price'].mean().plot(kind='bar') ``` -Graf bar harga vs jenis labu +Graf bar harga vs jenis labu Mari kita fokus buat sementara waktu hanya pada satu jenis labu, 'pie type', dan lihat kesan tarikh terhadap harga: @@ -153,7 +144,7 @@ Mari kita fokus buat sementara waktu hanya pada satu jenis labu, 'pie type', dan pie_pumpkins = new_pumpkins[new_pumpkins['Variety']=='PIE TYPE'] pie_pumpkins.plot.scatter('DayOfYear','Price') ``` -Plot penyebaran Harga vs. Hari dalam Tahun +Plot penyebaran Harga vs. Hari dalam Tahun Jika kita kini mengira korelasi antara `Harga` dan `HariDalamTahun` menggunakan fungsi `corr`, kita akan mendapat sesuatu seperti `-0.27` - yang bermaksud bahawa melatih model ramalan masuk akal. @@ -227,7 +218,7 @@ plt.scatter(X_test,y_test) plt.plot(X_test,pred) ``` -Regresi linear +Regresi linear ## Regresi Polinomial @@ -256,7 +247,7 @@ Menggunakan `PolynomialFeatures(2)` bermakna kita akan memasukkan semua polinomi Pipeline boleh digunakan dengan cara yang sama seperti objek `LinearRegression` asal, iaitu kita boleh `fit` pipeline, dan kemudian menggunakan `predict` untuk mendapatkan hasil ramalan. Berikut adalah graf yang menunjukkan data ujian, dan lengkung anggaran: -Regresi polinomial +Regresi polinomial Menggunakan Regresi Polinomial, kita boleh mendapatkan MSE yang sedikit lebih rendah dan penentuan yang lebih tinggi, tetapi tidak secara signifikan. Kita perlu mengambil kira ciri-ciri lain! @@ -274,7 +265,7 @@ Dalam dunia ideal, kita mahu dapat meramal harga untuk pelbagai jenis labu mengg Di sini anda boleh melihat bagaimana harga purata bergantung pada jenis: -Harga purata mengikut jenis +Harga purata mengikut jenis Untuk mengambil kira jenis, kita perlu menukarnya kepada bentuk numerik terlebih dahulu, atau **encode**. Terdapat beberapa cara kita boleh melakukannya: diff --git a/translations/ms/2-Regression/3-Linear/assignment.md b/translations/ms/2-Regression/3-Linear/assignment.md index 1c77891d7..ec0127db8 100644 --- a/translations/ms/2-Regression/3-Linear/assignment.md +++ b/translations/ms/2-Regression/3-Linear/assignment.md @@ -1,12 +1,3 @@ - # Membina Model Regresi ## Arahan diff --git a/translations/ms/2-Regression/3-Linear/solution/Julia/README.md b/translations/ms/2-Regression/3-Linear/solution/Julia/README.md index 26d05ff13..5da5c85e5 100644 --- a/translations/ms/2-Regression/3-Linear/solution/Julia/README.md +++ b/translations/ms/2-Regression/3-Linear/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/ms/2-Regression/4-Logistic/README.md b/translations/ms/2-Regression/4-Logistic/README.md index 85a5c2350..33e7b9fd8 100644 --- a/translations/ms/2-Regression/4-Logistic/README.md +++ b/translations/ms/2-Regression/4-Logistic/README.md @@ -1,12 +1,3 @@ - # Regresi Logistik untuk Meramal Kategori ![Infografik regresi logistik vs. regresi linear](../../../../2-Regression/4-Logistic/images/linear-vs-logistic.png) diff --git a/translations/ms/2-Regression/4-Logistic/assignment.md b/translations/ms/2-Regression/4-Logistic/assignment.md index a50080a69..129cbb3cc 100644 --- a/translations/ms/2-Regression/4-Logistic/assignment.md +++ b/translations/ms/2-Regression/4-Logistic/assignment.md @@ -1,12 +1,3 @@ - # Mencuba Semula Beberapa Regresi ## Arahan diff --git a/translations/ms/2-Regression/4-Logistic/solution/Julia/README.md b/translations/ms/2-Regression/4-Logistic/solution/Julia/README.md index 955efd113..5da5c85e5 100644 --- a/translations/ms/2-Regression/4-Logistic/solution/Julia/README.md +++ b/translations/ms/2-Regression/4-Logistic/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/ms/2-Regression/README.md b/translations/ms/2-Regression/README.md index 79c56025f..0db1511e3 100644 --- a/translations/ms/2-Regression/README.md +++ b/translations/ms/2-Regression/README.md @@ -1,12 +1,3 @@ - # Model regresi untuk pembelajaran mesin ## Topik serantau: Model regresi untuk harga labu di Amerika Utara 🎃 diff --git a/translations/ms/3-Web-App/1-Web-App/README.md b/translations/ms/3-Web-App/1-Web-App/README.md index 495f080b4..fb96017a6 100644 --- a/translations/ms/3-Web-App/1-Web-App/README.md +++ b/translations/ms/3-Web-App/1-Web-App/README.md @@ -1,12 +1,3 @@ - # Membina Aplikasi Web untuk Menggunakan Model ML Dalam pelajaran ini, anda akan melatih model ML menggunakan set data yang luar biasa: _Penampakan UFO sepanjang abad yang lalu_, yang diperoleh daripada pangkalan data NUFORC. diff --git a/translations/ms/3-Web-App/1-Web-App/assignment.md b/translations/ms/3-Web-App/1-Web-App/assignment.md index 96bc0d4b1..05bedb622 100644 --- a/translations/ms/3-Web-App/1-Web-App/assignment.md +++ b/translations/ms/3-Web-App/1-Web-App/assignment.md @@ -1,12 +1,3 @@ - # Cuba model yang berbeza ## Arahan diff --git a/translations/ms/3-Web-App/README.md b/translations/ms/3-Web-App/README.md index 94c5ace60..3bed48f07 100644 --- a/translations/ms/3-Web-App/README.md +++ b/translations/ms/3-Web-App/README.md @@ -1,12 +1,3 @@ - # Bina aplikasi web untuk menggunakan model ML anda Dalam bahagian kurikulum ini, anda akan diperkenalkan kepada topik ML yang diterapkan: bagaimana untuk menyimpan model Scikit-learn anda sebagai fail yang boleh digunakan untuk membuat ramalan dalam aplikasi web. Setelah model disimpan, anda akan belajar cara menggunakannya dalam aplikasi web yang dibina menggunakan Flask. Anda akan mula dengan mencipta model menggunakan data yang berkaitan dengan penampakan UFO! Kemudian, anda akan membina aplikasi web yang membolehkan anda memasukkan bilangan saat bersama nilai latitud dan longitud untuk meramalkan negara mana yang melaporkan melihat UFO. diff --git a/translations/ms/4-Classification/1-Introduction/README.md b/translations/ms/4-Classification/1-Introduction/README.md index b55f274a6..3b1d4f7fe 100644 --- a/translations/ms/4-Classification/1-Introduction/README.md +++ b/translations/ms/4-Classification/1-Introduction/README.md @@ -1,12 +1,3 @@ - # Pengenalan kepada klasifikasi Dalam empat pelajaran ini, anda akan meneroka fokus asas pembelajaran mesin klasik - _klasifikasi_. Kita akan menggunakan pelbagai algoritma klasifikasi dengan dataset tentang semua masakan hebat dari Asia dan India. Semoga anda lapar! diff --git a/translations/ms/4-Classification/1-Introduction/assignment.md b/translations/ms/4-Classification/1-Introduction/assignment.md index 6c7c3ba9f..4d9c131e7 100644 --- a/translations/ms/4-Classification/1-Introduction/assignment.md +++ b/translations/ms/4-Classification/1-Introduction/assignment.md @@ -1,12 +1,3 @@ - # Terokai kaedah pengelasan ## Arahan diff --git a/translations/ms/4-Classification/1-Introduction/solution/Julia/README.md b/translations/ms/4-Classification/1-Introduction/solution/Julia/README.md index 5636d7971..5da5c85e5 100644 --- a/translations/ms/4-Classification/1-Introduction/solution/Julia/README.md +++ b/translations/ms/4-Classification/1-Introduction/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/ms/4-Classification/2-Classifiers-1/README.md b/translations/ms/4-Classification/2-Classifiers-1/README.md index c3e27b8af..226ef5549 100644 --- a/translations/ms/4-Classification/2-Classifiers-1/README.md +++ b/translations/ms/4-Classification/2-Classifiers-1/README.md @@ -1,12 +1,3 @@ - # Pengelas Masakan 1 Dalam pelajaran ini, anda akan menggunakan dataset yang telah disimpan dari pelajaran sebelumnya yang penuh dengan data seimbang dan bersih mengenai masakan. diff --git a/translations/ms/4-Classification/2-Classifiers-1/assignment.md b/translations/ms/4-Classification/2-Classifiers-1/assignment.md index 9d8ea2324..1fc49a088 100644 --- a/translations/ms/4-Classification/2-Classifiers-1/assignment.md +++ b/translations/ms/4-Classification/2-Classifiers-1/assignment.md @@ -1,12 +1,3 @@ - # Kajian tentang penyelesai masalah ## Arahan diff --git a/translations/ms/4-Classification/2-Classifiers-1/solution/Julia/README.md b/translations/ms/4-Classification/2-Classifiers-1/solution/Julia/README.md index 93a82dec6..5da5c85e5 100644 --- a/translations/ms/4-Classification/2-Classifiers-1/solution/Julia/README.md +++ b/translations/ms/4-Classification/2-Classifiers-1/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/ms/4-Classification/3-Classifiers-2/README.md b/translations/ms/4-Classification/3-Classifiers-2/README.md index 1169a8324..968eadd00 100644 --- a/translations/ms/4-Classification/3-Classifiers-2/README.md +++ b/translations/ms/4-Classification/3-Classifiers-2/README.md @@ -1,12 +1,3 @@ - # Pengelas Masakan 2 Dalam pelajaran klasifikasi kedua ini, anda akan meneroka lebih banyak cara untuk mengklasifikasikan data berangka. Anda juga akan mempelajari implikasi memilih satu pengelas berbanding yang lain. diff --git a/translations/ms/4-Classification/3-Classifiers-2/assignment.md b/translations/ms/4-Classification/3-Classifiers-2/assignment.md index 0ab21d96c..9939116d4 100644 --- a/translations/ms/4-Classification/3-Classifiers-2/assignment.md +++ b/translations/ms/4-Classification/3-Classifiers-2/assignment.md @@ -1,12 +1,3 @@ - # Parameter Play ## Arahan diff --git a/translations/ms/4-Classification/3-Classifiers-2/solution/Julia/README.md b/translations/ms/4-Classification/3-Classifiers-2/solution/Julia/README.md index 964d85e78..5da5c85e5 100644 --- a/translations/ms/4-Classification/3-Classifiers-2/solution/Julia/README.md +++ b/translations/ms/4-Classification/3-Classifiers-2/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/ms/4-Classification/4-Applied/README.md b/translations/ms/4-Classification/4-Applied/README.md index f88964c52..529cf74b4 100644 --- a/translations/ms/4-Classification/4-Applied/README.md +++ b/translations/ms/4-Classification/4-Applied/README.md @@ -1,12 +1,3 @@ - # Membina Aplikasi Web Pencadang Masakan Dalam pelajaran ini, anda akan membina model klasifikasi menggunakan beberapa teknik yang telah dipelajari dalam pelajaran sebelumnya dan dataset masakan yang lazat yang digunakan sepanjang siri ini. Selain itu, anda akan membina aplikasi web kecil untuk menggunakan model yang disimpan, dengan memanfaatkan runtime web Onnx. diff --git a/translations/ms/4-Classification/4-Applied/assignment.md b/translations/ms/4-Classification/4-Applied/assignment.md index 2bbea28a6..d32c7721e 100644 --- a/translations/ms/4-Classification/4-Applied/assignment.md +++ b/translations/ms/4-Classification/4-Applied/assignment.md @@ -1,12 +1,3 @@ - # Bina sistem cadangan ## Arahan diff --git a/translations/ms/4-Classification/README.md b/translations/ms/4-Classification/README.md index 33c8d6708..48de95c51 100644 --- a/translations/ms/4-Classification/README.md +++ b/translations/ms/4-Classification/README.md @@ -1,12 +1,3 @@ - # Memulakan dengan klasifikasi ## Topik serantau: Masakan Asia dan India yang lazat 🍜 diff --git a/translations/ms/5-Clustering/1-Visualize/README.md b/translations/ms/5-Clustering/1-Visualize/README.md index 4a500d577..c2f6e91ff 100644 --- a/translations/ms/5-Clustering/1-Visualize/README.md +++ b/translations/ms/5-Clustering/1-Visualize/README.md @@ -1,12 +1,3 @@ - # Pengenalan kepada pengelompokan Pengelompokan adalah sejenis [Pembelajaran Tanpa Pengawasan](https://wikipedia.org/wiki/Unsupervised_learning) yang mengandaikan bahawa dataset tidak berlabel atau inputnya tidak dipadankan dengan output yang telah ditentukan. Ia menggunakan pelbagai algoritma untuk menyusun data yang tidak berlabel dan menyediakan kumpulan berdasarkan corak yang dikenalpasti dalam data. diff --git a/translations/ms/5-Clustering/1-Visualize/assignment.md b/translations/ms/5-Clustering/1-Visualize/assignment.md index 090b05aae..b86234390 100644 --- a/translations/ms/5-Clustering/1-Visualize/assignment.md +++ b/translations/ms/5-Clustering/1-Visualize/assignment.md @@ -1,12 +1,3 @@ - # Kajian Visualisasi Lain untuk Pengelompokan ## Arahan diff --git a/translations/ms/5-Clustering/1-Visualize/solution/Julia/README.md b/translations/ms/5-Clustering/1-Visualize/solution/Julia/README.md index 4c7551bb0..5da5c85e5 100644 --- a/translations/ms/5-Clustering/1-Visualize/solution/Julia/README.md +++ b/translations/ms/5-Clustering/1-Visualize/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/ms/5-Clustering/2-K-Means/README.md b/translations/ms/5-Clustering/2-K-Means/README.md index 03a4d11ba..efa206367 100644 --- a/translations/ms/5-Clustering/2-K-Means/README.md +++ b/translations/ms/5-Clustering/2-K-Means/README.md @@ -1,12 +1,3 @@ - # Pengelompokan K-Means ## [Kuiz Pra-Kuliah](https://ff-quizzes.netlify.app/en/ml/) diff --git a/translations/ms/5-Clustering/2-K-Means/assignment.md b/translations/ms/5-Clustering/2-K-Means/assignment.md index 93b568fff..e1f9caa27 100644 --- a/translations/ms/5-Clustering/2-K-Means/assignment.md +++ b/translations/ms/5-Clustering/2-K-Means/assignment.md @@ -1,12 +1,3 @@ - # Cuba kaedah pengelompokan yang berbeza ## Arahan diff --git a/translations/ms/5-Clustering/2-K-Means/solution/Julia/README.md b/translations/ms/5-Clustering/2-K-Means/solution/Julia/README.md index 552134e95..5da5c85e5 100644 --- a/translations/ms/5-Clustering/2-K-Means/solution/Julia/README.md +++ b/translations/ms/5-Clustering/2-K-Means/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/ms/5-Clustering/README.md b/translations/ms/5-Clustering/README.md index bcdd405bc..ea31d0b2d 100644 --- a/translations/ms/5-Clustering/README.md +++ b/translations/ms/5-Clustering/README.md @@ -1,12 +1,3 @@ - # Model pengelompokan untuk pembelajaran mesin Pengelompokan adalah tugas pembelajaran mesin di mana ia mencari objek yang menyerupai satu sama lain dan mengelompokkannya ke dalam kumpulan yang dipanggil kluster. Apa yang membezakan pengelompokan daripada pendekatan lain dalam pembelajaran mesin ialah prosesnya berlaku secara automatik, malah boleh dikatakan ia bertentangan dengan pembelajaran terarah. diff --git a/translations/ms/6-NLP/1-Introduction-to-NLP/README.md b/translations/ms/6-NLP/1-Introduction-to-NLP/README.md index d022d1b67..aad6cf17a 100644 --- a/translations/ms/6-NLP/1-Introduction-to-NLP/README.md +++ b/translations/ms/6-NLP/1-Introduction-to-NLP/README.md @@ -1,12 +1,3 @@ - # Pengenalan kepada pemprosesan bahasa semula jadi Pelajaran ini merangkumi sejarah ringkas dan konsep penting tentang *pemprosesan bahasa semula jadi*, satu cabang daripada *linguistik komputer*. diff --git a/translations/ms/6-NLP/1-Introduction-to-NLP/assignment.md b/translations/ms/6-NLP/1-Introduction-to-NLP/assignment.md index 0f131de3a..7b65511a2 100644 --- a/translations/ms/6-NLP/1-Introduction-to-NLP/assignment.md +++ b/translations/ms/6-NLP/1-Introduction-to-NLP/assignment.md @@ -1,12 +1,3 @@ - # Cari bot ## Arahan diff --git a/translations/ms/6-NLP/2-Tasks/README.md b/translations/ms/6-NLP/2-Tasks/README.md index f328eb663..fb1b9d8ec 100644 --- a/translations/ms/6-NLP/2-Tasks/README.md +++ b/translations/ms/6-NLP/2-Tasks/README.md @@ -1,12 +1,3 @@ - # Tugas Pemprosesan Bahasa Semula Jadi dan Teknik-Tekniknya Untuk kebanyakan *tugas pemprosesan bahasa semula jadi*, teks yang akan diproses mesti dipecahkan, diperiksa, dan hasilnya disimpan atau dirujuk silang dengan peraturan dan set data. Tugas-tugas ini membolehkan pengaturcara mendapatkan _makna_ atau _niat_ atau hanya _kekerapan_ istilah dan perkataan dalam teks. diff --git a/translations/ms/6-NLP/2-Tasks/assignment.md b/translations/ms/6-NLP/2-Tasks/assignment.md index e92b60e56..3d1fcf2a3 100644 --- a/translations/ms/6-NLP/2-Tasks/assignment.md +++ b/translations/ms/6-NLP/2-Tasks/assignment.md @@ -1,12 +1,3 @@ - # Membuat Bot Berinteraksi Balik ## Arahan diff --git a/translations/ms/6-NLP/3-Translation-Sentiment/README.md b/translations/ms/6-NLP/3-Translation-Sentiment/README.md index bc07942fa..9756e0a25 100644 --- a/translations/ms/6-NLP/3-Translation-Sentiment/README.md +++ b/translations/ms/6-NLP/3-Translation-Sentiment/README.md @@ -1,12 +1,3 @@ - # Terjemahan dan analisis sentimen dengan ML Dalam pelajaran sebelumnya, anda telah belajar cara membina bot asas menggunakan `TextBlob`, sebuah perpustakaan yang menggabungkan ML di belakang tabir untuk melaksanakan tugas NLP asas seperti pengekstrakan frasa kata nama. Satu lagi cabaran penting dalam linguistik komputer ialah _terjemahan_ yang tepat bagi ayat daripada satu bahasa lisan atau tulisan kepada bahasa lain. diff --git a/translations/ms/6-NLP/3-Translation-Sentiment/assignment.md b/translations/ms/6-NLP/3-Translation-Sentiment/assignment.md index 33ca59f40..bf34daade 100644 --- a/translations/ms/6-NLP/3-Translation-Sentiment/assignment.md +++ b/translations/ms/6-NLP/3-Translation-Sentiment/assignment.md @@ -1,12 +1,3 @@ - # Lesen Puitis ## Arahan diff --git a/translations/ms/6-NLP/3-Translation-Sentiment/solution/Julia/README.md b/translations/ms/6-NLP/3-Translation-Sentiment/solution/Julia/README.md index f92ddc4ee..5da5c85e5 100644 --- a/translations/ms/6-NLP/3-Translation-Sentiment/solution/Julia/README.md +++ b/translations/ms/6-NLP/3-Translation-Sentiment/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/ms/6-NLP/3-Translation-Sentiment/solution/R/README.md b/translations/ms/6-NLP/3-Translation-Sentiment/solution/R/README.md index 97b72ccc4..b862c19a4 100644 --- a/translations/ms/6-NLP/3-Translation-Sentiment/solution/R/README.md +++ b/translations/ms/6-NLP/3-Translation-Sentiment/solution/R/README.md @@ -1,12 +1,3 @@ - ini adalah pemegang tempat sementara --- diff --git a/translations/ms/6-NLP/4-Hotel-Reviews-1/README.md b/translations/ms/6-NLP/4-Hotel-Reviews-1/README.md index c638a876b..72a1b11c8 100644 --- a/translations/ms/6-NLP/4-Hotel-Reviews-1/README.md +++ b/translations/ms/6-NLP/4-Hotel-Reviews-1/README.md @@ -1,12 +1,3 @@ - # Analisis Sentimen dengan Ulasan Hotel - Memproses Data Dalam bahagian ini, anda akan menggunakan teknik yang dipelajari dalam pelajaran sebelumnya untuk melakukan analisis data eksploratori pada set data yang besar. Setelah anda memahami kegunaan pelbagai kolum dengan baik, anda akan belajar: diff --git a/translations/ms/6-NLP/4-Hotel-Reviews-1/assignment.md b/translations/ms/6-NLP/4-Hotel-Reviews-1/assignment.md index 05452e42c..013853e37 100644 --- a/translations/ms/6-NLP/4-Hotel-Reviews-1/assignment.md +++ b/translations/ms/6-NLP/4-Hotel-Reviews-1/assignment.md @@ -1,12 +1,3 @@ - # NLTK ## Arahan diff --git a/translations/ms/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md b/translations/ms/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md index d73eed82a..5da5c85e5 100644 --- a/translations/ms/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md +++ b/translations/ms/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/ms/6-NLP/4-Hotel-Reviews-1/solution/R/README.md b/translations/ms/6-NLP/4-Hotel-Reviews-1/solution/R/README.md index bf572c4c6..b862c19a4 100644 --- a/translations/ms/6-NLP/4-Hotel-Reviews-1/solution/R/README.md +++ b/translations/ms/6-NLP/4-Hotel-Reviews-1/solution/R/README.md @@ -1,12 +1,3 @@ - ini adalah pemegang tempat sementara --- diff --git a/translations/ms/6-NLP/5-Hotel-Reviews-2/README.md b/translations/ms/6-NLP/5-Hotel-Reviews-2/README.md index 53954eb53..8df2d0eba 100644 --- a/translations/ms/6-NLP/5-Hotel-Reviews-2/README.md +++ b/translations/ms/6-NLP/5-Hotel-Reviews-2/README.md @@ -1,12 +1,3 @@ - # Analisis Sentimen dengan Ulasan Hotel Sekarang setelah anda meneroka dataset dengan terperinci, tiba masanya untuk menapis kolum dan menggunakan teknik NLP pada dataset untuk mendapatkan wawasan baru tentang hotel. diff --git a/translations/ms/6-NLP/5-Hotel-Reviews-2/assignment.md b/translations/ms/6-NLP/5-Hotel-Reviews-2/assignment.md index 63373dd8d..9464dcdbe 100644 --- a/translations/ms/6-NLP/5-Hotel-Reviews-2/assignment.md +++ b/translations/ms/6-NLP/5-Hotel-Reviews-2/assignment.md @@ -1,12 +1,3 @@ - # Cuba dataset yang berbeza ## Arahan diff --git a/translations/ms/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md b/translations/ms/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md index c960a07b9..5da5c85e5 100644 --- a/translations/ms/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md +++ b/translations/ms/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/ms/6-NLP/5-Hotel-Reviews-2/solution/R/README.md b/translations/ms/6-NLP/5-Hotel-Reviews-2/solution/R/README.md index ff60393ce..b862c19a4 100644 --- a/translations/ms/6-NLP/5-Hotel-Reviews-2/solution/R/README.md +++ b/translations/ms/6-NLP/5-Hotel-Reviews-2/solution/R/README.md @@ -1,12 +1,3 @@ - ini adalah pemegang tempat sementara --- diff --git a/translations/ms/6-NLP/README.md b/translations/ms/6-NLP/README.md index 92a2b29ff..de40a8342 100644 --- a/translations/ms/6-NLP/README.md +++ b/translations/ms/6-NLP/README.md @@ -1,12 +1,3 @@ - # Memulakan dengan pemprosesan bahasa semula jadi Pemprosesan bahasa semula jadi (NLP) adalah keupayaan program komputer untuk memahami bahasa manusia seperti yang dituturkan dan ditulis -- dirujuk sebagai bahasa semula jadi. Ia merupakan komponen kecerdasan buatan (AI). NLP telah wujud selama lebih daripada 50 tahun dan berakar umbi dalam bidang linguistik. Keseluruhan bidang ini bertujuan membantu mesin memahami dan memproses bahasa manusia. Ini kemudian boleh digunakan untuk melaksanakan tugas seperti semakan ejaan atau terjemahan mesin. Ia mempunyai pelbagai aplikasi dunia nyata dalam beberapa bidang, termasuk penyelidikan perubatan, enjin carian dan kecerdasan perniagaan. diff --git a/translations/ms/6-NLP/data/README.md b/translations/ms/6-NLP/data/README.md index ce5ec5fc5..003b49b17 100644 --- a/translations/ms/6-NLP/data/README.md +++ b/translations/ms/6-NLP/data/README.md @@ -1,12 +1,3 @@ - Muat turun data ulasan hotel ke folder ini. --- diff --git a/translations/ms/7-TimeSeries/1-Introduction/README.md b/translations/ms/7-TimeSeries/1-Introduction/README.md index 2fa6a871c..353ff7514 100644 --- a/translations/ms/7-TimeSeries/1-Introduction/README.md +++ b/translations/ms/7-TimeSeries/1-Introduction/README.md @@ -1,12 +1,3 @@ - # Pengenalan kepada ramalan siri masa ![Ringkasan siri masa dalam sketchnote](../../../../sketchnotes/ml-timeseries.png) diff --git a/translations/ms/7-TimeSeries/1-Introduction/assignment.md b/translations/ms/7-TimeSeries/1-Introduction/assignment.md index 6f4fb0743..9d26bc7fa 100644 --- a/translations/ms/7-TimeSeries/1-Introduction/assignment.md +++ b/translations/ms/7-TimeSeries/1-Introduction/assignment.md @@ -1,12 +1,3 @@ - # Visualisasi Beberapa Lagi Siri Masa ## Arahan diff --git a/translations/ms/7-TimeSeries/1-Introduction/solution/Julia/README.md b/translations/ms/7-TimeSeries/1-Introduction/solution/Julia/README.md index 22471a6c6..5da5c85e5 100644 --- a/translations/ms/7-TimeSeries/1-Introduction/solution/Julia/README.md +++ b/translations/ms/7-TimeSeries/1-Introduction/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/ms/7-TimeSeries/1-Introduction/solution/R/README.md b/translations/ms/7-TimeSeries/1-Introduction/solution/R/README.md index f95ff8680..b862c19a4 100644 --- a/translations/ms/7-TimeSeries/1-Introduction/solution/R/README.md +++ b/translations/ms/7-TimeSeries/1-Introduction/solution/R/README.md @@ -1,12 +1,3 @@ - ini adalah pemegang tempat sementara --- diff --git a/translations/ms/7-TimeSeries/2-ARIMA/README.md b/translations/ms/7-TimeSeries/2-ARIMA/README.md index 98c7915c1..b3d07b98d 100644 --- a/translations/ms/7-TimeSeries/2-ARIMA/README.md +++ b/translations/ms/7-TimeSeries/2-ARIMA/README.md @@ -1,12 +1,3 @@ - # Ramalan siri masa dengan ARIMA Dalam pelajaran sebelumnya, anda telah mempelajari sedikit tentang ramalan siri masa dan memuatkan dataset yang menunjukkan turun naik beban elektrik sepanjang tempoh masa. diff --git a/translations/ms/7-TimeSeries/2-ARIMA/assignment.md b/translations/ms/7-TimeSeries/2-ARIMA/assignment.md index 0da13867f..98ae5b1d0 100644 --- a/translations/ms/7-TimeSeries/2-ARIMA/assignment.md +++ b/translations/ms/7-TimeSeries/2-ARIMA/assignment.md @@ -1,12 +1,3 @@ - # Model ARIMA baharu ## Arahan diff --git a/translations/ms/7-TimeSeries/2-ARIMA/solution/Julia/README.md b/translations/ms/7-TimeSeries/2-ARIMA/solution/Julia/README.md index 32fd7393b..5da5c85e5 100644 --- a/translations/ms/7-TimeSeries/2-ARIMA/solution/Julia/README.md +++ b/translations/ms/7-TimeSeries/2-ARIMA/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/ms/7-TimeSeries/2-ARIMA/solution/R/README.md b/translations/ms/7-TimeSeries/2-ARIMA/solution/R/README.md index 8d6166e61..0fd0043d9 100644 --- a/translations/ms/7-TimeSeries/2-ARIMA/solution/R/README.md +++ b/translations/ms/7-TimeSeries/2-ARIMA/solution/R/README.md @@ -1,12 +1,3 @@ - ini adalah pemegang tempat sementara --- diff --git a/translations/ms/7-TimeSeries/3-SVR/README.md b/translations/ms/7-TimeSeries/3-SVR/README.md index 35a62e3a0..4edb17121 100644 --- a/translations/ms/7-TimeSeries/3-SVR/README.md +++ b/translations/ms/7-TimeSeries/3-SVR/README.md @@ -1,12 +1,3 @@ - # Ramalan Siri Masa dengan Support Vector Regressor Dalam pelajaran sebelumnya, anda telah belajar cara menggunakan model ARIMA untuk membuat ramalan siri masa. Kini anda akan melihat model Support Vector Regressor, iaitu model regresi yang digunakan untuk meramalkan data berterusan. diff --git a/translations/ms/7-TimeSeries/3-SVR/assignment.md b/translations/ms/7-TimeSeries/3-SVR/assignment.md index 14e03e9f5..9fa252701 100644 --- a/translations/ms/7-TimeSeries/3-SVR/assignment.md +++ b/translations/ms/7-TimeSeries/3-SVR/assignment.md @@ -1,12 +1,3 @@ - # Model SVR Baru ## Arahan [^1] diff --git a/translations/ms/7-TimeSeries/README.md b/translations/ms/7-TimeSeries/README.md index 785eb6432..80f14a33b 100644 --- a/translations/ms/7-TimeSeries/README.md +++ b/translations/ms/7-TimeSeries/README.md @@ -1,12 +1,3 @@ - # Pengenalan kepada ramalan siri masa Apakah ramalan siri masa? Ia adalah tentang meramalkan peristiwa masa depan dengan menganalisis trend masa lalu. diff --git a/translations/ms/8-Reinforcement/1-QLearning/README.md b/translations/ms/8-Reinforcement/1-QLearning/README.md index b3508ab63..3ae432147 100644 --- a/translations/ms/8-Reinforcement/1-QLearning/README.md +++ b/translations/ms/8-Reinforcement/1-QLearning/README.md @@ -1,12 +1,3 @@ - # Pengenalan kepada Pembelajaran Pengukuhan dan Q-Learning ![Ringkasan pembelajaran pengukuhan dalam pembelajaran mesin dalam bentuk sketchnote](../../../../sketchnotes/ml-reinforcement.png) diff --git a/translations/ms/8-Reinforcement/1-QLearning/assignment.md b/translations/ms/8-Reinforcement/1-QLearning/assignment.md index bb68d4718..58c49ffd3 100644 --- a/translations/ms/8-Reinforcement/1-QLearning/assignment.md +++ b/translations/ms/8-Reinforcement/1-QLearning/assignment.md @@ -1,12 +1,3 @@ - # Dunia yang Lebih Realistik Dalam situasi kita, Peter dapat bergerak hampir tanpa merasa letih atau lapar. Dalam dunia yang lebih realistik, dia perlu duduk dan berehat dari semasa ke semasa, serta makan untuk mengisi tenaga. Mari kita jadikan dunia kita lebih realistik dengan melaksanakan peraturan berikut: diff --git a/translations/ms/8-Reinforcement/1-QLearning/solution/Julia/README.md b/translations/ms/8-Reinforcement/1-QLearning/solution/Julia/README.md index 5f95f720d..5da5c85e5 100644 --- a/translations/ms/8-Reinforcement/1-QLearning/solution/Julia/README.md +++ b/translations/ms/8-Reinforcement/1-QLearning/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/ms/8-Reinforcement/1-QLearning/solution/R/README.md b/translations/ms/8-Reinforcement/1-QLearning/solution/R/README.md index 15f83fcc7..b862c19a4 100644 --- a/translations/ms/8-Reinforcement/1-QLearning/solution/R/README.md +++ b/translations/ms/8-Reinforcement/1-QLearning/solution/R/README.md @@ -1,12 +1,3 @@ - ini adalah pemegang tempat sementara --- diff --git a/translations/ms/8-Reinforcement/2-Gym/README.md b/translations/ms/8-Reinforcement/2-Gym/README.md index 05564f5fe..b1707984b 100644 --- a/translations/ms/8-Reinforcement/2-Gym/README.md +++ b/translations/ms/8-Reinforcement/2-Gym/README.md @@ -1,12 +1,3 @@ - ## Prasyarat Dalam pelajaran ini, kita akan menggunakan perpustakaan bernama **OpenAI Gym** untuk mensimulasikan pelbagai **persekitaran**. Anda boleh menjalankan kod pelajaran ini secara tempatan (contohnya dari Visual Studio Code), di mana simulasi akan dibuka dalam tetingkap baru. Apabila menjalankan kod secara dalam talian, anda mungkin perlu membuat beberapa penyesuaian pada kod, seperti yang diterangkan [di sini](https://towardsdatascience.com/rendering-openai-gym-envs-on-binder-and-google-colab-536f99391cc7). diff --git a/translations/ms/8-Reinforcement/2-Gym/assignment.md b/translations/ms/8-Reinforcement/2-Gym/assignment.md index cdef26fa8..ce7ea4c0a 100644 --- a/translations/ms/8-Reinforcement/2-Gym/assignment.md +++ b/translations/ms/8-Reinforcement/2-Gym/assignment.md @@ -1,12 +1,3 @@ - # Latih Mountain Car [OpenAI Gym](http://gym.openai.com) telah direka sedemikian rupa sehingga semua persekitaran menyediakan API yang sama - iaitu kaedah yang sama `reset`, `step` dan `render`, serta abstraksi yang sama untuk **ruang tindakan** dan **ruang pemerhatian**. Oleh itu, seharusnya mungkin untuk menyesuaikan algoritma pembelajaran pengukuhan yang sama kepada persekitaran yang berbeza dengan perubahan kod yang minimum. diff --git a/translations/ms/8-Reinforcement/2-Gym/solution/Julia/README.md b/translations/ms/8-Reinforcement/2-Gym/solution/Julia/README.md index bbbd2e21d..fb8802d6e 100644 --- a/translations/ms/8-Reinforcement/2-Gym/solution/Julia/README.md +++ b/translations/ms/8-Reinforcement/2-Gym/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/ms/8-Reinforcement/2-Gym/solution/R/README.md b/translations/ms/8-Reinforcement/2-Gym/solution/R/README.md index e15b2d587..b862c19a4 100644 --- a/translations/ms/8-Reinforcement/2-Gym/solution/R/README.md +++ b/translations/ms/8-Reinforcement/2-Gym/solution/R/README.md @@ -1,12 +1,3 @@ - ini adalah pemegang tempat sementara --- diff --git a/translations/ms/8-Reinforcement/README.md b/translations/ms/8-Reinforcement/README.md index cef0cc968..bb62198a7 100644 --- a/translations/ms/8-Reinforcement/README.md +++ b/translations/ms/8-Reinforcement/README.md @@ -1,12 +1,3 @@ - # Pengenalan kepada pembelajaran pengukuhan Pembelajaran pengukuhan, RL, dianggap sebagai salah satu paradigma pembelajaran mesin asas, selain pembelajaran terselia dan pembelajaran tidak terselia. RL berkaitan dengan membuat keputusan: memberikan keputusan yang tepat atau sekurang-kurangnya belajar daripadanya. diff --git a/translations/ms/9-Real-World/1-Applications/README.md b/translations/ms/9-Real-World/1-Applications/README.md index a0b45140b..60f4d51b2 100644 --- a/translations/ms/9-Real-World/1-Applications/README.md +++ b/translations/ms/9-Real-World/1-Applications/README.md @@ -1,12 +1,3 @@ - # Postscript: Pembelajaran Mesin di Dunia Sebenar ![Ringkasan pembelajaran mesin di dunia sebenar dalam sketchnote](../../../../sketchnotes/ml-realworld.png) diff --git a/translations/ms/9-Real-World/1-Applications/assignment.md b/translations/ms/9-Real-World/1-Applications/assignment.md index f51a732fb..ca37c4728 100644 --- a/translations/ms/9-Real-World/1-Applications/assignment.md +++ b/translations/ms/9-Real-World/1-Applications/assignment.md @@ -1,12 +1,3 @@ - # Pemburuan Harta Karun ML ## Arahan diff --git a/translations/ms/9-Real-World/2-Debugging-ML-Models/README.md b/translations/ms/9-Real-World/2-Debugging-ML-Models/README.md index d936d0076..9d32a2b4b 100644 --- a/translations/ms/9-Real-World/2-Debugging-ML-Models/README.md +++ b/translations/ms/9-Real-World/2-Debugging-ML-Models/README.md @@ -1,12 +1,3 @@ - # Postscript: Penyahpepijatan Model dalam Pembelajaran Mesin menggunakan komponen papan pemuka AI Bertanggungjawab ## [Kuiz pra-kuliah](https://ff-quizzes.netlify.app/en/ml/) diff --git a/translations/ms/9-Real-World/2-Debugging-ML-Models/assignment.md b/translations/ms/9-Real-World/2-Debugging-ML-Models/assignment.md index 963a8931e..597158c8c 100644 --- a/translations/ms/9-Real-World/2-Debugging-ML-Models/assignment.md +++ b/translations/ms/9-Real-World/2-Debugging-ML-Models/assignment.md @@ -1,12 +1,3 @@ - # Terokai papan pemuka AI Bertanggungjawab (RAI) ## Arahan diff --git a/translations/ms/9-Real-World/README.md b/translations/ms/9-Real-World/README.md index 51753aa1f..399743af2 100644 --- a/translations/ms/9-Real-World/README.md +++ b/translations/ms/9-Real-World/README.md @@ -1,12 +1,3 @@ - # Postscript: Aplikasi dunia sebenar pembelajaran mesin klasik Dalam bahagian kurikulum ini, anda akan diperkenalkan kepada beberapa aplikasi dunia sebenar pembelajaran mesin klasik. Kami telah mencari di internet untuk mendapatkan kertas putih dan artikel tentang aplikasi yang menggunakan strategi ini, sambil mengelakkan rangkaian neural, pembelajaran mendalam dan AI sebanyak mungkin. Ketahui bagaimana pembelajaran mesin digunakan dalam sistem perniagaan, aplikasi ekologi, kewangan, seni dan budaya, dan banyak lagi. diff --git a/translations/ms/AGENTS.md b/translations/ms/AGENTS.md index f54ae2c3c..7d50c6621 100644 --- a/translations/ms/AGENTS.md +++ b/translations/ms/AGENTS.md @@ -1,12 +1,3 @@ - # AGENTS.md ## Gambaran Projek diff --git a/translations/ms/CODE_OF_CONDUCT.md b/translations/ms/CODE_OF_CONDUCT.md index 87d3de2c5..fffcdb082 100644 --- a/translations/ms/CODE_OF_CONDUCT.md +++ b/translations/ms/CODE_OF_CONDUCT.md @@ -1,12 +1,3 @@ - # Kod Etika Sumber Terbuka Microsoft Projek ini telah mengguna pakai [Kod Etika Sumber Terbuka Microsoft](https://opensource.microsoft.com/codeofconduct/). diff --git a/translations/ms/CONTRIBUTING.md b/translations/ms/CONTRIBUTING.md index 8d1b610a3..dcf1109e8 100644 --- a/translations/ms/CONTRIBUTING.md +++ b/translations/ms/CONTRIBUTING.md @@ -1,12 +1,3 @@ - # Menyumbang Projek ini mengalu-alukan sumbangan dan cadangan. Kebanyakan sumbangan memerlukan anda diff --git a/translations/ms/README.md b/translations/ms/README.md index 634f162a8..7d4fcb1e9 100644 --- a/translations/ms/README.md +++ b/translations/ms/README.md @@ -1,84 +1,74 @@ - [![Lesen GitHub](https://img.shields.io/github/license/microsoft/ML-For-Beginners.svg)](https://github.com/microsoft/ML-For-Beginners/blob/master/LICENSE) [![Penyumbang GitHub](https://img.shields.io/github/contributors/microsoft/ML-For-Beginners.svg)](https://GitHub.com/microsoft/ML-For-Beginners/graphs/contributors/) [![Isu GitHub](https://img.shields.io/github/issues/microsoft/ML-For-Beginners.svg)](https://GitHub.com/microsoft/ML-For-Beginners/issues/) [![Permintaan tarik GitHub](https://img.shields.io/github/issues-pr/microsoft/ML-For-Beginners.svg)](https://GitHub.com/microsoft/ML-For-Beginners/pulls/) -[![Selamat datang PR](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com) +[![PRs Dialu-alukan](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com) [![Penonton GitHub](https://img.shields.io/github/watchers/microsoft/ML-For-Beginners.svg?style=social&label=Watch)](https://GitHub.com/microsoft/ML-For-Beginners/watchers/) -[![Garpu GitHub](https://img.shields.io/github/forks/microsoft/ML-For-Beginners.svg?style=social&label=Fork)](https://GitHub.com/microsoft/ML-For-Beginners/network/) +[![Cawangan GitHub](https://img.shields.io/github/forks/microsoft/ML-For-Beginners.svg?style=social&label=Fork)](https://GitHub.com/microsoft/ML-For-Beginners/network/) [![Bintang GitHub](https://img.shields.io/github/stars/microsoft/ML-For-Beginners.svg?style=social&label=Star)](https://GitHub.com/microsoft/ML-For-Beginners/stargazers/) ### 🌐 Sokongan Pelbagai Bahasa -#### Disokong melalui Tindakan GitHub (Automatik & Sentiasa Dikemas Kini) +#### Disokong melalui Tindakan GitHub (Automatik & Sentiasa Terkini) -[Arab](../ar/README.md) | [Bengali](../bn/README.md) | [Bulgaria](../bg/README.md) | [Burma (Myanmar)](../my/README.md) | [Cina (Ringkas)](../zh/README.md) | [Cina (Tradisional, Hong Kong)](../hk/README.md) | [Cina (Tradisional, Macau)](../mo/README.md) | [Cina (Tradisional, Taiwan)](../tw/README.md) | [Croatia](../hr/README.md) | [Szech](../cs/README.md) | [Denmark](../da/README.md) | [Belanda](../nl/README.md) | [Estonia](../et/README.md) | [Finland](../fi/README.md) | [Perancis](../fr/README.md) | [Jerman](../de/README.md) | [Yunani](../el/README.md) | [Ibrani](../he/README.md) | [Hindi](../hi/README.md) | [Hungary](../hu/README.md) | [Indonesia](../id/README.md) | [Itali](../it/README.md) | [Jepun](../ja/README.md) | [Kannada](../kn/README.md) | [Korea](../ko/README.md) | [Lithuania](../lt/README.md) | [Melayu](./README.md) | [Malayalam](../ml/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Pidgin Nigeria](../pcm/README.md) | [Norway](../no/README.md) | [Parsi (Farsi)](../fa/README.md) | [Poland](../pl/README.md) | [Portugis (Brazil)](../br/README.md) | [Portugis (Portugal)](../pt/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Romania](../ro/README.md) | [Rusia](../ru/README.md) | [Serbia (Cyrillic)](../sr/README.md) | [Slovak](../sk/README.md) | [Slovenia](../sl/README.md) | [Sepanyol](../es/README.md) | [Swahili](../sw/README.md) | [Sweden](../sv/README.md) | [Tagalog (Filipina)](../tl/README.md) | [Tamil](../ta/README.md) | [Telugu](../te/README.md) | [Thai](../th/README.md) | [Turki](../tr/README.md) | [Ukraine](../uk/README.md) | [Urdu](../ur/README.md) | [Vietnam](../vi/README.md) +[Arab](../ar/README.md) | [Benggali](../bn/README.md) | [Bulgaria](../bg/README.md) | [Burma (Myanmar)](../my/README.md) | [Cina (Ringkas)](../zh-CN/README.md) | [Cina (Tradisional, Hong Kong)](../zh-HK/README.md) | [Cina (Tradisional, Macau)](../zh-MO/README.md) | [Cina (Tradisional, Taiwan)](../zh-TW/README.md) | [Kroasia](../hr/README.md) | [Czech](../cs/README.md) | [Denmark](../da/README.md) | [Belanda](../nl/README.md) | [Estonia](../et/README.md) | [Finland](../fi/README.md) | [Perancis](../fr/README.md) | [Jerman](../de/README.md) | [Greek](../el/README.md) | [Ibrani](../he/README.md) | [Hindi](../hi/README.md) | [Hungaria](../hu/README.md) | [Indonesia](../id/README.md) | [Itali](../it/README.md) | [Jepun](../ja/README.md) | [Kannada](../kn/README.md) | [Korea](../ko/README.md) | [Lithuania](../lt/README.md) | [Melayu](./README.md) | [Malayalam](../ml/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Nigerian Pidgin](../pcm/README.md) | [Norwegian](../no/README.md) | [Parsi (Farsi)](../fa/README.md) | [Poland](../pl/README.md) | [Portugis (Brazil)](../pt-BR/README.md) | [Portugis (Portugal)](../pt-PT/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Romania](../ro/README.md) | [Rusia](../ru/README.md) | [Serbia (Cyrillic)](../sr/README.md) | [Slovak](../sk/README.md) | [Slovenia](../sl/README.md) | [Sepanyol](../es/README.md) | [Swahili](../sw/README.md) | [Sweden](../sv/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Tamil](../ta/README.md) | [Telugu](../te/README.md) | [Thai](../th/README.md) | [Turki](../tr/README.md) | [Ukrainian](../uk/README.md) | [Urdu](../ur/README.md) | [Vietnam](../vi/README.md) -> **Lebih suka Klon Secara Tempatan?** +> **Lebih suka Klon Tempatan?** -> Repositori ini termasuk 50+ terjemahan bahasa yang secara signifikan meningkatkan saiz muat turun. Untuk klon tanpa terjemahan, gunakan sparse checkout: +> Repositori ini mengandungi 50+ terjemahan bahasa yang meningkatkan saiz muat turun dengan ketara. Untuk klon tanpa terjemahan, gunakan sparse checkout: > ```bash > git clone --filter=blob:none --sparse https://github.com/microsoft/ML-For-Beginners.git > cd ML-For-Beginners > git sparse-checkout set --no-cone '/*' '!translations' '!translated_images' > ``` -> Ini memberi anda segala yang anda perlukan untuk menyelesaikan kursus dengan muat turun yang jauh lebih cepat. +> Ini memberi anda segala yang anda perlukan untuk melengkapkan kursus dengan muat turun yang jauh lebih pantas. #### Sertai Komuniti Kami [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -Kami sedang menjalankan siri Discord belajar dengan AI, ketahui lebih lanjut dan sertai kami di [Siri Belajar dengan AI](https://aka.ms/learnwithai/discord) dari 18 - 30 September, 2025. Anda akan mendapat petua dan trik menggunakan GitHub Copilot untuk Sains Data. +Kami mempunyai siri belajar dengan AI Discord yang sedang berlangsung, pelajari lebih lanjut dan sertai kami di [Siri Belajar dengan AI](https://aka.ms/learnwithai/discord) dari 18 - 30 September, 2025. Anda akan mendapat tips dan trik menggunakan GitHub Copilot untuk Sains Data. -![Siri belajar dengan AI](../../../../translated_images/ms/3.9b58fd8d6c373c20.webp) +![Siri Belajar dengan AI](../../translated_images/ms/3.9b58fd8d6c373c20.webp) # Pembelajaran Mesin untuk Pemula - Kurikulum -> 🌍 Melancong ke seluruh dunia sambil meneroka Pembelajaran Mesin melalui budaya dunia 🌍 +> 🌍 Jelajah seluruh dunia semasa kita meneroka Pembelajaran Mesin melalui budaya dunia 🌍 -Penggerak Awan di Microsoft dengan sukacitanya menawarkan kurikulum 12 minggu, 26 pelajaran mengenai **Pembelajaran Mesin**. Dalam kurikulum ini, anda akan mempelajari apa yang kadang-kala dipanggil **pembelajaran mesin klasik**, menggunakan terutamanya Scikit-learn sebagai perpustakaan dan mengelakkan pembelajaran mendalam, yang dibincangkan dalam [kurikulum AI untuk Pemula](https://aka.ms/ai4beginners) kami. Gabungkan pelajaran ini dengan ['Kurikulum Sains Data untuk Pemula'](https://aka.ms/ds4beginners) kami juga! +Penyokong Awan di Microsoft dengan sukacitanya menawarkan kurikulum 12 minggu, 26 pelajaran yang semuanya mengenai **Pembelajaran Mesin**. Dalam kurikulum ini, anda akan belajar tentang apa yang kadang-kadang dipanggil **pembelajaran mesin klasik**, menggunakan terutamanya Scikit-learn sebagai perpustakaan dan mengelakkan pembelajaran mendalam, yang dibahas dalam [kurikulum AI untuk Pemula kami](https://aka.ms/ai4beginners). Padankan pelajaran ini dengan ['Kurikulum Sains Data untuk Pemula'](https://aka.ms/ds4beginners), juga! -Bersama kami mengembara ke seluruh dunia sambil menerapkan teknik klasik ini pada data dari banyak kawasan di dunia. Setiap pelajaran merangkumi kuiz sebelum dan selepas pelajaran, arahan bertulis untuk menyelesaikan pelajaran, penyelesaian, tugasan, dan banyak lagi. Pendekatan berasaskan projek kami membolehkan anda belajar sambil membina, cara terbukti untuk kemahiran baru 'melekat'. +Bepergianlah bersama kami ke seluruh dunia semasa kami menerapkan teknik klasik ini pada data dari banyak kawasan dunia. Setiap pelajaran termasuk kuiz pra dan pasca pelajaran, arahan bertulis untuk melengkapkan pelajaran, penyelesaian, tugasan, dan banyak lagi. Pedagogi berasaskan projek kami membolehkan anda belajar sambil membina, satu cara terbukti untuk kemahiran baru 'melekat'. -**✍️ Terima kasih yang tidak terhingga kepada penulis kami** Jen Looper, Stephen Howell, Francesca Lazzeri, Tomomi Imura, Cassie Breviu, Dmitry Soshnikov, Chris Noring, Anirban Mukherjee, Ornella Altunyan, Ruth Yakubu dan Amy Boyd +**✍️ Terima kasih yang tidak terhingga kepada pengarang kami** Jen Looper, Stephen Howell, Francesca Lazzeri, Tomomi Imura, Cassie Breviu, Dmitry Soshnikov, Chris Noring, Anirban Mukherjee, Ornella Altunyan, Ruth Yakubu dan Amy Boyd -**🎨 Terima kasih juga kepada pelukis ilustrasi kami** Tomomi Imura, Dasani Madipalli, dan Jen Looper +**🎨 Terima kasih juga kepada pelukis kami** Tomomi Imura, Dasani Madipalli, dan Jen Looper -**🙏 Terima kasih khas 🙏 kepada penulis, penyemak dan penyumbang kandungan Duta Pelajar Microsoft kami**, terutamanya Rishit Dagli, Muhammad Sakib Khan Inan, Rohan Raj, Alexandru Petrescu, Abhishek Jaiswal, Nawrin Tabassum, Ioan Samuila, dan Snigdha Agarwal +**🙏 Terima kasih istimewa 🙏 kepada pengarang, penyemak dan penyumbang kandungan Duta Pelajar Microsoft kami**, terutamanya Rishit Dagli, Muhammad Sakib Khan Inan, Rohan Raj, Alexandru Petrescu, Abhishek Jaiswal, Nawrin Tabassum, Ioan Samuila, dan Snigdha Agarwal **🤩 Penghargaan tambahan kepada Duta Pelajar Microsoft Eric Wanjau, Jasleen Sondhi, dan Vidushi Gupta untuk pelajaran R kami!** -# Mulakan +# Memulakan -Ikuti langkah-langkah ini: -1. **Fork Repositori**: Klik butang "Fork" di sudut kanan atas halaman ini. +Ikuti langkah berikut: +1. **Fork Repositori**: Klik pada butang "Fork" di penjuru atas kanan halaman ini. 2. **Klon Repositori**: `git clone https://github.com/microsoft/ML-For-Beginners.git` > [cari semua sumber tambahan untuk kursus ini dalam koleksi Microsoft Learn kami](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) -> 🔧 **Perlukan bantuan?** Semak [Panduan Penyelesaian Masalah](TROUBLESHOOTING.md) kami untuk penyelesaian masalah biasa berkaitan pemasangan, persediaan, dan menjalankan pelajaran. +> 🔧 **Perlukan bantuan?** Semak [Panduan Penyelesaian Masalah](TROUBLESHOOTING.md) kami untuk penyelesaian isu biasa dengan pemasangan, penyediaan, dan menjalankan pelajaran. +**[Pelajar](https://aka.ms/student-page)**, untuk menggunakan kurikulum ini, buatlah cabang (fork) repositori keseluruhan ke akaun GitHub anda sendiri dan selesaikan latihan secara sendiri atau dalam kumpulan: -**[Pelajar](https://aka.ms/student-page)**, untuk menggunakan kurikulum ini, fork seluruh repositori ke akaun GitHub anda sendiri dan selesaikan latihan sendiri atau bersama kumpulan: - -- Mulakan dengan kuiz pra-ceramah. -- Baca kuliah dan lengkapkan aktiviti, berhenti dan renungkan setiap pemeriksaan pengetahuan. -- Cuba cipta projek dengan memahami pelajaran daripada menjalankan kod penyelesaian; walau bagaimanapun kod itu tersedia dalam folder `/solution` dalam setiap pelajaran berorientasikan projek. -- Ambil kuiz selepas kuliah. -- Selesaikan cabaran. -- Selesaikan tugasan. -- Selepas menamatkan satu kumpulan pelajaran, lawati [Papan Perbincangan](https://github.com/microsoft/ML-For-Beginners/discussions) dan "belajar dengan lantang" dengan mengisi rubrik PAT yang sesuai. 'PAT' adalah Alat Penilaian Kemajuan yang merupakan rubrik anda mengisinya untuk meningkatkan pembelajaran. Anda juga boleh memberi reaksi kepada PAT lain supaya kita boleh belajar bersama. +- Mulakan dengan kuiz pemanasan pra-ceramah. +- Baca kuliah dan lengkapkan aktiviti, berhenti seketika dan renungkan pada setiap pemeriksaan pengetahuan. +- Cuba cipta projek dengan memahami pelajaran dan bukannya menjalankan kod penyelesaian; namun kod tersebut tersedia dalam folder `/solution` di setiap pelajaran berorientasikan projek. +- Ambil kuiz pasca kuliah. +- Lengkapkan cabaran. +- Lengkapkan tugasan. +- Selepas melengkapkan satu kumpulan pelajaran, lawati [Papan Perbincangan](https://github.com/microsoft/ML-For-Beginners/discussions) dan "belajar secara lantang" dengan mengisi rubrik PAT yang sesuai. 'PAT' ialah Alat Penilaian Kemajuan yang merupakan rubrik yang anda isi untuk memajukan pembelajaran anda. Anda juga boleh bertindak balas kepada PAT lain supaya kita boleh belajar bersama. > Untuk pengajian lanjut, kami mengesyorkan mengikuti modul dan laluan pembelajaran [Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/k7o7tg1gp306q4?WT.mc_id=academic-77952-leestott) ini. @@ -86,11 +76,11 @@ Ikuti langkah-langkah ini: --- -## Panduan Video +## Video panduan -Sesetengah pelajaran tersedia dalam bentuk video pendek. Anda boleh menemui kesemua ini secara sebaris dalam pelajaran, atau di [senarai main ML untuk Pemula di saluran YouTube Microsoft Developer](https://aka.ms/ml-beginners-videos) dengan mengklik imej di bawah. +Sesetengah pelajaran tersedia sebagai video bentuk ringkas. Anda boleh menemui semuanya dalam pelajaran, atau di [senarai main ML for Beginners di saluran YouTube Microsoft Developer](https://aka.ms/ml-beginners-videos) dengan mengklik imej di bawah. -[![Sepanduk ML untuk pemula](../../../../translated_images/ms/ml-for-beginners-video-banner.63f694a100034bc6.webp)](https://aka.ms/ml-beginners-videos) +[![Banner ML untuk pemula](../../translated_images/ms/ml-for-beginners-video-banner.63f694a100034bc6.webp)](https://aka.ms/ml-beginners-videos) --- @@ -98,76 +88,76 @@ Sesetengah pelajaran tersedia dalam bentuk video pendek. Anda boleh menemui kese [![Video promosi](../../images/ml.gif)](https://youtu.be/Tj1XWrDSYJU) -**GIF oleh** [Mohit Jaisal](https://linkedin.com/in/mohitjaisal) +**Gif oleh** [Mohit Jaisal](https://linkedin.com/in/mohitjaisal) -> 🎥 Klik imej di atas untuk video tentang projek dan orang yang menciptanya! +> 🎥 Klik imej di atas untuk video mengenai projek dan orang yang menciptakannya! --- ## Pedagogi -Kami memilih dua prinsip pedagogi ketika membangunkan kurikulum ini: memastikan ia berasaskan projek yang praktikal dan termasuk kuiz yang kerap. Selain itu, kurikulum ini mempunyai tema umum untuk memberikan keseragaman. +Kami memilih dua prinsip pedagogi semasa membina kurikulum ini: memastikan ia berasaskan **projek praktikal** dan termasuk **kuiz kerap**. Selain itu, kurikulum ini mempunyai **tema** yang sama untuk memberikan kesatuan. -Dengan memastikan kandungan selari dengan projek, proses pembelajaran menjadi lebih menarik bagi pelajar dan pengekalan konsep akan bertambah baik. Selain itu, kuiz rendah risiko sebelum kelas menetapkan niat pelajar untuk mempelajari topik, sementara kuiz kedua selepas kelas memastikan pengekalan yang lebih baik. Kurikulum ini direka supaya fleksibel dan menyeronokkan dan boleh diambil secara keseluruhan atau sebahagian. Projek bermula kecil dan menjadi semakin kompleks pada penghujung kitaran 12 minggu. Kurikulum ini juga termasuk posskrip mengenai aplikasi dunia sebenar ML, yang boleh digunakan sebagai kredit tambahan atau sebagai asas perbincangan. +Dengan memastikan kandungan selari dengan projek, prosesnya menjadi lebih menarik untuk pelajar dan pengekalan konsep akan dipertingkatkan. Selain itu, kuiz berisiko rendah sebelum kelas menetapkan niat pelajar untuk belajar topik, sementara kuiz kedua selepas kelas memastikan pengekalan lebih lanjut. Kurikulum ini direka supaya fleksibel dan menyeronokkan serta boleh diambil secara keseluruhan atau sebahagian. Projek bermula kecil dan menjadi semakin rumit menjelang akhir kitaran 12 minggu. Kurikulum ini juga mengandungi posskrip mengenai aplikasi nyata ML, yang boleh digunakan sebagai kredit tambahan atau sebagai asas untuk perbincangan. -> Dapatkan [Kod Etika](CODE_OF_CONDUCT.md), [Penyumbangan](CONTRIBUTING.md), [Terjemahan](TRANSLATIONS.md), dan panduan [Penyelesaian Masalah](TROUBLESHOOTING.md) kami. Kami mengalu-alukan maklum balas membina anda! +> Temui [Kod Etika](CODE_OF_CONDUCT.md), [Menyumbang](CONTRIBUTING.md), [Terjemahan](TRANSLATIONS.md), dan [Penyelesaian Masalah](TROUBLESHOOTING.md) panduan kami. Kami mengalu-alukan maklum balas membina anda! -## Setiap pelajaran merangkumi +## Setiap pelajaran mengandungi -- nota lakaran pilihan +- sketchnote pilihan - video tambahan pilihan -- panduan video (sesetengah pelajaran sahaja) +- video panduan (sesetengah pelajaran sahaja) - [kuiz pemanasan pra-ceramah](https://ff-quizzes.netlify.app/en/ml/) - pelajaran bertulis -- untuk pelajaran berasaskan projek, panduan langkah demi langkah untuk membina projek +- untuk pelajaran berasaskan projek, panduan langkah demi langkah cara membina projek - pemeriksaan pengetahuan - cabaran - bacaan tambahan - tugasan - [kuiz pasca-ceramah](https://ff-quizzes.netlify.app/en/ml/) -> **Nota tentang bahasa**: Pelajaran ini kebanyakannya ditulis dalam Python, tetapi banyak juga tersedia dalam R. Untuk melengkapkan pelajaran R, pergi ke folder `/solution` dan cari pelajaran R. Ia termasuk sambungan .rmd yang mewakili fail **R Markdown** yang boleh dijelaskan sebagai gabungan `keping kod` (dalam R atau bahasa lain) dan `header YAML` (yang mengarahkan bagaimana format output seperti PDF) dalam `dokumen Markdown`. Oleh itu, ia menjadi kerangka pengarang contoh untuk sains data kerana ia membolehkan anda menggabungkan kod, outputnya, dan pemikiran anda dengan membenarkan anda menulisnya dalam Markdown. Selain itu, dokumen R Markdown boleh dihasilkan ke format output seperti PDF, HTML, atau Word. -> **Nota mengenai kuiz**: Semua kuiz terkandung dalam [folder Aplikasi Kuiz](../../quiz-app), dengan jumlah 52 kuiz, setiap satu mengandungi tiga soalan. Ia dihubungkan dari dalam pelajaran tetapi aplikasi kuiz boleh dijalankan secara tempatan; ikut arahan dalam folder `quiz-app` untuk hos tempatan atau jalankan ke Azure. - -| Nombor Pelajaran | Topik | Pengelompokan Pelajaran | Objektif Pembelajaran | Pelajaran Berkaitan | Pengarang | -| :---------------: | :------------------------------------------------------------: | :----------------------------------------------------------: | ----------------------------------------------------------------------------------------------------------------------------- | :-----------------------------------------------------------------------------------------------------------------------------------------: | :----------------------------------------------------: | -| 01 | Pengenalan kepada pembelajaran mesin | [Pengenalan](1-Introduction/README.md) | Pelajari konsep asas di sebalik pembelajaran mesin | [Pelajaran](1-Introduction/1-intro-to-ML/README.md) | Muhammad | -| 02 | Sejarah pembelajaran mesin | [Pengenalan](1-Introduction/README.md) | Pelajari sejarah di sebalik bidang ini | [Pelajaran](1-Introduction/2-history-of-ML/README.md) | Jen dan Amy | -| 03 | Keadilan dan pembelajaran mesin | [Pengenalan](1-Introduction/README.md) | Apa isu falsafah penting tentang keadilan yang harus dipertimbangkan pelajar ketika membina dan menggunakan model ML? | [Pelajaran](1-Introduction/3-fairness/README.md) | Tomomi | -| 04 | Teknik untuk pembelajaran mesin | [Pengenalan](1-Introduction/README.md) | Teknik apa yang digunakan penyelidik ML untuk membina model ML? | [Pelajaran](1-Introduction/4-techniques-of-ML/README.md) | Chris dan Jen | -| 05 | Pengenalan kepada regresi | [Regresi](2-Regression/README.md) | Mula menggunakan Python dan Scikit-learn untuk model regresi | [Python](2-Regression/1-Tools/README.md) • [R](../../2-Regression/1-Tools/solution/R/lesson_1.html) | Jen • Eric Wanjau | -| 06 | Harga labu Amerika Utara 🎃 | [Regresi](2-Regression/README.md) | Visualisasikan dan bersihkan data sebagai persediaan untuk ML | [Python](2-Regression/2-Data/README.md) • [R](../../2-Regression/2-Data/solution/R/lesson_2.html) | Jen • Eric Wanjau | -| 07 | Harga labu Amerika Utara 🎃 | [Regresi](2-Regression/README.md) | Bina model regresi linear dan polinomial | [Python](2-Regression/3-Linear/README.md) • [R](../../2-Regression/3-Linear/solution/R/lesson_3.html) | Jen dan Dmitry • Eric Wanjau | -| 08 | Harga labu Amerika Utara 🎃 | [Regresi](2-Regression/README.md) | Bina model regresi logistik | [Python](2-Regression/4-Logistic/README.md) • [R](../../2-Regression/4-Logistic/solution/R/lesson_4.html) | Jen • Eric Wanjau | -| 09 | Aplikasi Web 🔌 | [Aplikasi Web](3-Web-App/README.md) | Bina aplikasi web untuk menggunakan model yang telah dilatih | [Python](3-Web-App/1-Web-App/README.md) | Jen | -| 10 | Pengenalan kepada klasifikasi | [Klasifikasi](4-Classification/README.md) | Bersihkan, sediakan, dan visualisasikan data anda; pengenalan kepada klasifikasi | [Python](4-Classification/1-Introduction/README.md) • [R](../../4-Classification/1-Introduction/solution/R/lesson_10.html) | Jen dan Cassie • Eric Wanjau | -| 11 | Masakan Asia dan India yang lazat 🍜 | [Klasifikasi](4-Classification/README.md) | Pengenalan kepada pengelasan | [Python](4-Classification/2-Classifiers-1/README.md) • [R](../../4-Classification/2-Classifiers-1/solution/R/lesson_11.html) | Jen dan Cassie • Eric Wanjau | -| 12 | Masakan Asia dan India yang lazat 🍜 | [Klasifikasi](4-Classification/README.md) | Lebih banyak pengelasan | [Python](4-Classification/3-Classifiers-2/README.md) • [R](../../4-Classification/3-Classifiers-2/solution/R/lesson_12.html) | Jen dan Cassie • Eric Wanjau | -| 13 | Masakan Asia dan India yang lazat 🍜 | [Klasifikasi](4-Classification/README.md) | Bina aplikasi web pencadang menggunakan model anda | [Python](4-Classification/4-Applied/README.md) | Jen | -| 14 | Pengenalan kepada pengelompokan | [Pengelompokan](5-Clustering/README.md) | Bersihkan, sediakan, dan visualisasikan data anda; pengenalan kepada pengelompokan | [Python](5-Clustering/1-Visualize/README.md) • [R](../../5-Clustering/1-Visualize/solution/R/lesson_14.html) | Jen • Eric Wanjau | -| 15 | Meneroka citarasa muzik Nigeria 🎧 | [Pengelompokan](5-Clustering/README.md) | Terokai kaedah K-Means clustering | [Python](5-Clustering/2-K-Means/README.md) • [R](../../5-Clustering/2-K-Means/solution/R/lesson_15.html) | Jen • Eric Wanjau | -| 16 | Pengenalan kepada pemprosesan bahasa semula jadi ☕️ | [Pemprosesan bahasa semula jadi](6-NLP/README.md) | Pelajari asas mengenai NLP dengan membina bot mudah | [Python](6-NLP/1-Introduction-to-NLP/README.md) | Stephen | -| 17 | Tugasan umum NLP ☕️ | [Pemprosesan bahasa semula jadi](6-NLP/README.md) | Mendalami pengetahuan NLP anda dengan memahami tugasan umum yang diperlukan ketika mengendalikan struktur bahasa | [Python](6-NLP/2-Tasks/README.md) | Stephen | -| 18 | Penterjemahan dan analisis sentimen ♥️ | [Pemprosesan bahasa semula jadi](6-NLP/README.md) | Penterjemahan dan analisis sentimen dengan Jane Austen | [Python](6-NLP/3-Translation-Sentiment/README.md) | Stephen | -| 19 | Hotel romantik di Eropah ♥️ | [Pemprosesan bahasa semula jadi](6-NLP/README.md) | Analisis sentimen dengan ulasan hotel 1 | [Python](6-NLP/4-Hotel-Reviews-1/README.md) | Stephen | -| 20 | Hotel romantik di Eropah ♥️ | [Pemprosesan bahasa semula jadi](6-NLP/README.md) | Analisis sentimen dengan ulasan hotel 2 | [Python](6-NLP/5-Hotel-Reviews-2/README.md) | Stephen | -| 21 | Pengenalan kepada ramalan siri masa | [Siri masa](7-TimeSeries/README.md) | Pengenalan kepada ramalan siri masa | [Python](7-TimeSeries/1-Introduction/README.md) | Francesca | -| 22 | ⚡️ Penggunaan Kuasa Dunia ⚡️ - ramalan siri masa dengan ARIMA | [Siri masa](7-TimeSeries/README.md) | Ramalan siri masa dengan ARIMA | [Python](7-TimeSeries/2-ARIMA/README.md) | Francesca | -| 23 | ⚡️ Penggunaan Kuasa Dunia ⚡️ - ramalan siri masa dengan SVR | [Siri masa](7-TimeSeries/README.md) | Ramalan siri masa dengan Support Vector Regressor | [Python](7-TimeSeries/3-SVR/README.md) | Anirban | -| 24 | Pengenalan kepada pembelajaran penguatan | [Pembelajaran penguatan](8-Reinforcement/README.md) | Pengenalan kepada pembelajaran penguatan dengan Q-Learning | [Python](8-Reinforcement/1-QLearning/README.md) | Dmitry | -| 25 | Bantu Peter mengelak dari serigala! 🐺 | [Pembelajaran penguatan](8-Reinforcement/README.md) | Pembelajaran penguatan Gym | [Python](8-Reinforcement/2-Gym/README.md) | Dmitry | -| Catatan Akhir | Senario dan aplikasi ML Dunia Sebenar | [ML di Alam Liar](9-Real-World/README.md) | Aplikasi ML klasik dunia sebenar yang menarik dan mendedahkan | [Pelajaran](9-Real-World/1-Applications/README.md) | Pasukan | -| Catatan Akhir | Penyahpepijatan Model dalam ML menggunakan papan pemuka RAI | [ML di Alam Liar](9-Real-World/README.md) | Penyahpepijatan Model dalam Pembelajaran Mesin menggunakan komponen papan pemuka Responsible AI | [Pelajaran](9-Real-World/2-Debugging-ML-Models/README.md) | Ruth Yakubu | +> **Nota tentang bahasa**: Pelajaran ini terutama ditulis dalam Python, tetapi banyak juga tersedia dalam R. Untuk melengkapkan pelajaran R, pergi ke folder `/solution` dan cari pelajaran R. Ia termasuk peluasan .rmd yang mewakili fail **R Markdown** yang boleh didefinisikan sebagai gabungan `chunk kod` (R atau bahasa lain) dan `header YAML` (yang mengarahkan cara format output seperti PDF) dalam `dokumen Markdown`. Oleh itu, ia berfungsi sebagai rangka kerja penulisan contoh untuk sains data kerana ia membolehkan anda menggabungkan kod anda, outputnya, dan pemikiran anda dengan membolehkan anda menuliskannya dalam Markdown. Selain itu, dokumen R Markdown boleh dirender ke format output seperti PDF, HTML, atau Word. +> **Satu nota tentang kuiz**: Semua kuiz terkandung dalam [folder Quiz App](../../quiz-app), untuk 52 kuiz keseluruhan dengan tiga soalan setiap satu. Ia dipautkan dari dalam pelajaran tetapi aplikasi kuiz boleh dijalankan secara tempatan; ikut arahan dalam folder `quiz-app` untuk menghos atau melancarkan ke Azure secara tempatan. + +| Nombor Pelajaran | Topik | Pengelompokan Pelajaran | Objektif Pembelajaran | Pelajaran Berkaitan | Penulis | +| :--------------: | :------------------------------------------------------------: | :----------------------------------------------------------: | ------------------------------------------------------------------------------------------------------------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------: | +| 01 | Pengenalan kepada pembelajaran mesin | [Pengenalan](1-Introduction/README.md) | Pelajari konsep asas di sebalik pembelajaran mesin | [Pelajaran](1-Introduction/1-intro-to-ML/README.md) | Muhammad | +| 02 | Sejarah pembelajaran mesin | [Pengenalan](1-Introduction/README.md) | Pelajari sejarah di sebalik bidang ini | [Pelajaran](1-Introduction/2-history-of-ML/README.md) | Jen dan Amy | +| 03 | Keadilan dan pembelajaran mesin | [Pengenalan](1-Introduction/README.md) | Apakah isu falsafah penting mengenai keadilan yang perlu dipertimbangkan oleh pelajar semasa membina dan menggunakan model ML? | [Pelajaran](1-Introduction/3-fairness/README.md) | Tomomi | +| 04 | Teknik untuk pembelajaran mesin | [Pengenalan](1-Introduction/README.md) | Apakah teknik yang digunakan penyelidik ML untuk membina model ML? | [Pelajaran](1-Introduction/4-techniques-of-ML/README.md) | Chris dan Jen | +| 05 | Pengenalan kepada regresi | [Regresi](2-Regression/README.md) | Mula dengan Python dan Scikit-learn untuk model regresi | [Python](2-Regression/1-Tools/README.md) • [R](../../2-Regression/1-Tools/solution/R/lesson_1.html) | Jen • Eric Wanjau | +| 06 | Harga labu Amerika Utara 🎃 | [Regresi](2-Regression/README.md) | Visualisasikan dan bersihkan data sebagai persiapan untuk ML | [Python](2-Regression/2-Data/README.md) • [R](../../2-Regression/2-Data/solution/R/lesson_2.html) | Jen • Eric Wanjau | +| 07 | Harga labu Amerika Utara 🎃 | [Regresi](2-Regression/README.md) | Bina model regresi linear dan polinomial | [Python](2-Regression/3-Linear/README.md) • [R](../../2-Regression/3-Linear/solution/R/lesson_3.html) | Jen dan Dmitry • Eric Wanjau | +| 08 | Harga labu Amerika Utara 🎃 | [Regresi](2-Regression/README.md) | Bina model regresi logistik | [Python](2-Regression/4-Logistic/README.md) • [R](../../2-Regression/4-Logistic/solution/R/lesson_4.html) | Jen • Eric Wanjau | +| 09 | Aplikasi Web 🔌 | [Aplikasi Web](3-Web-App/README.md) | Bina aplikasi web untuk menggunakan model yang telah dilatih | [Python](3-Web-App/1-Web-App/README.md) | Jen | +| 10 | Pengenalan kepada klasifikasi | [Klasifikasi](4-Classification/README.md) | Bersihkan, sediakan, dan visualisasikan data anda; pengenalan kepada klasifikasi | [Python](4-Classification/1-Introduction/README.md) • [R](../../4-Classification/1-Introduction/solution/R/lesson_10.html) | Jen dan Cassie • Eric Wanjau | +| 11 | Masakan Asia dan India yang lazat 🍜 | [Klasifikasi](4-Classification/README.md) | Pengenalan kepada pengklasifikasi | [Python](4-Classification/2-Classifiers-1/README.md) • [R](../../4-Classification/2-Classifiers-1/solution/R/lesson_11.html) | Jen dan Cassie • Eric Wanjau | +| 12 | Masakan Asia dan India yang lazat 🍜 | [Klasifikasi](4-Classification/README.md) | Lebih banyak pengklasifikasi | [Python](4-Classification/3-Classifiers-2/README.md) • [R](../../4-Classification/3-Classifiers-2/solution/R/lesson_12.html) | Jen dan Cassie • Eric Wanjau | +| 13 | Masakan Asia dan India yang lazat 🍜 | [Klasifikasi](4-Classification/README.md) | Bina aplikasi web pemesejan menggunakan model anda | [Python](4-Classification/4-Applied/README.md) | Jen | +| 14 | Pengenalan kepada pengelompokan | [Pengelompokan](5-Clustering/README.md) | Bersihkan, sediakan, dan visualisasikan data anda; Pengenalan kepada pengelompokan | [Python](5-Clustering/1-Visualize/README.md) • [R](../../5-Clustering/1-Visualize/solution/R/lesson_14.html) | Jen • Eric Wanjau | +| 15 | Meneroka Selera Muzik Nigeria 🎧 | [Pengelompokan](5-Clustering/README.md) | Terokai kaedah pengelompokan K-Means | [Python](5-Clustering/2-K-Means/README.md) • [R](../../5-Clustering/2-K-Means/solution/R/lesson_15.html) | Jen • Eric Wanjau | +| 16 | Pengenalan kepada pemprosesan bahasa semula jadi ☕️ | [Pemprosesan bahasa semula jadi](6-NLP/README.md) | Pelajari asas NLP dengan membina bot mudah | [Python](6-NLP/1-Introduction-to-NLP/README.md) | Stephen | +| 17 | Tugasan NLP Lazim ☕️ | [Pemprosesan bahasa semula jadi](6-NLP/README.md) | Mendalami pengetahuan NLP anda dengan memahami tugasan biasa yang diperlukan apabila berurusan dengan struktur bahasa | [Python](6-NLP/2-Tasks/README.md) | Stephen | +| 18 | Terjemahan dan analisis sentimen ♥️ | [Pemprosesan bahasa semula jadi](6-NLP/README.md) | Terjemahan dan analisis sentimen dengan Jane Austen | [Python](6-NLP/3-Translation-Sentiment/README.md) | Stephen | +| 19 | Hotel romantik di Eropah ♥️ | [Pemprosesan bahasa semula jadi](6-NLP/README.md) | Analisis sentimen dengan ulasan hotel 1 | [Python](6-NLP/4-Hotel-Reviews-1/README.md) | Stephen | +| 20 | Hotel romantik di Eropah ♥️ | [Pemprosesan bahasa semula jadi](6-NLP/README.md) | Analisis sentimen dengan ulasan hotel 2 | [Python](6-NLP/5-Hotel-Reviews-2/README.md) | Stephen | +| 21 | Pengenalan kepada peramalan siri masa | [Siri Masa](7-TimeSeries/README.md) | Pengenalan kepada peramalan siri masa | [Python](7-TimeSeries/1-Introduction/README.md) | Francesca | +| 22 | ⚡️ Penggunaan Kuasa Dunia ⚡️ - peramalan siri masa dengan ARIMA | [Siri Masa](7-TimeSeries/README.md) | Peramalan siri masa dengan ARIMA | [Python](7-TimeSeries/2-ARIMA/README.md) | Francesca | +| 23 | ⚡️ Penggunaan Kuasa Dunia ⚡️ - peramalan siri masa dengan SVR | [Siri Masa](7-TimeSeries/README.md) | Peramalan siri masa dengan Support Vector Regressor | [Python](7-TimeSeries/3-SVR/README.md) | Anirban | +| 24 | Pengenalan kepada pembelajaran penguatan | [Pembelajaran Penguatan](8-Reinforcement/README.md) | Pengenalan kepada pembelajaran penguatan dengan Q-Learning | [Python](8-Reinforcement/1-QLearning/README.md) | Dmitry | +| 25 | Bantu Peter elak serigala! 🐺 | [Pembelajaran Penguatan](8-Reinforcement/README.md) | Pembelajaran penguatan Gym | [Python](8-Reinforcement/2-Gym/README.md) | Dmitry | +| Penutup | Senario dan aplikasi ML Dunia Sebenar | [ML di Alam Liar](9-Real-World/README.md) | Aplikasi dunia sebenar yang menarik dan mendedahkan ML klasik | [Pelajaran](9-Real-World/1-Applications/README.md) | Pasukan | +| Penutup | Penyahpepijatan Model dalam ML menggunakan papan pemuka RAI | [ML di Alam Liar](9-Real-World/README.md) | Penyahpepijatan Model dalam Pembelajaran Mesin menggunakan komponen papan pemuka Responsible AI | [Pelajaran](9-Real-World/2-Debugging-ML-Models/README.md) | Ruth Yakubu | > [cari semua sumber tambahan untuk kursus ini dalam koleksi Microsoft Learn kami](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) ## Akses luar talian -Anda boleh menjalankan dokumentasi ini secara luar talian dengan menggunakan [Docsify](https://docsify.js.org/#/). Cawangan repo ini, [pasang Docsify](https://docsify.js.org/#/quickstart) pada mesin tempatan anda, dan kemudian di folder akar repo ini, taip `docsify serve`. Laman web akan dihidangkan pada port 3000 di localhost anda: `localhost:3000`. +Anda boleh menjalankan dokumentasi ini secara luar talian dengan menggunakan [Docsify](https://docsify.js.org/#/). Buat forking repo ini, [pasang Docsify](https://docsify.js.org/#/quickstart) pada mesin tempatan anda, kemudian di folder akar repo ini, taip `docsify serve`. Laman web akan dihidangkan pada port 3000 di localhost anda: `localhost:3000`. ## PDF -Cari pdf kurikulum dengan pautan [di sini](https://microsoft.github.io/ML-For-Beginners/pdf/readme.pdf). +Dapatkan pdf kurikulum dengan pautan [di sini](https://microsoft.github.io/ML-For-Beginners/pdf/readme.pdf). ## 🎒 Kursus Lain @@ -176,57 +166,57 @@ Pasukan kami menghasilkan kursus lain! Semak: ### LangChain -[![LangChain4j untuk Pemula](https://img.shields.io/badge/LangChain4j%20for%20Beginners-22C55E?style=for-the-badge&&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchain4j-for-beginners) -[![LangChain.js untuk Pemula](https://img.shields.io/badge/LangChain.js%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchainjs-for-beginners?WT.mc_id=m365-94501-dwahlin) +[![LangChain4j for Beginners](https://img.shields.io/badge/LangChain4j%20for%20Beginners-22C55E?style=for-the-badge&&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchain4j-for-beginners) +[![LangChain.js for Beginners](https://img.shields.io/badge/LangChain.js%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=0553D6)](https://aka.ms/langchainjs-for-beginners?WT.mc_id=m365-94501-dwahlin) --- -### Azure / Edge / MCP / Agen -[![AZD untuk Pemula](https://img.shields.io/badge/AZD%20for%20Beginners-0078D4?style=for-the-badge&labelColor=E5E7EB&color=0078D4)](https://github.com/microsoft/AZD-for-beginners?WT.mc_id=academic-105485-koreyst) -[![Edge AI untuk Pemula](https://img.shields.io/badge/Edge%20AI%20for%20Beginners-00B8E4?style=for-the-badge&labelColor=E5E7EB&color=00B8E4)](https://github.com/microsoft/edgeai-for-beginners?WT.mc_id=academic-105485-koreyst) -[![MCP untuk Pemula](https://img.shields.io/badge/MCP%20for%20Beginners-009688?style=for-the-badge&labelColor=E5E7EB&color=009688)](https://github.com/microsoft/mcp-for-beginners?WT.mc_id=academic-105485-koreyst) -[![Agen AI untuk Pemula](https://img.shields.io/badge/AI%20Agents%20for%20Beginners-00C49A?style=for-the-badge&labelColor=E5E7EB&color=00C49A)](https://github.com/microsoft/ai-agents-for-beginners?WT.mc_id=academic-105485-koreyst) +### Azure / Edge / MCP / Ejen +[![AZD for Beginners](https://img.shields.io/badge/AZD%20for%20Beginners-0078D4?style=for-the-badge&labelColor=E5E7EB&color=0078D4)](https://github.com/microsoft/AZD-for-beginners?WT.mc_id=academic-105485-koreyst) +[![Edge AI for Beginners](https://img.shields.io/badge/Edge%20AI%20for%20Beginners-00B8E4?style=for-the-badge&labelColor=E5E7EB&color=00B8E4)](https://github.com/microsoft/edgeai-for-beginners?WT.mc_id=academic-105485-koreyst) +[![MCP for Beginners](https://img.shields.io/badge/MCP%20for%20Beginners-009688?style=for-the-badge&labelColor=E5E7EB&color=009688)](https://github.com/microsoft/mcp-for-beginners?WT.mc_id=academic-105485-koreyst) +[![AI Agents for Beginners](https://img.shields.io/badge/AI%20Agents%20for%20Beginners-00C49A?style=for-the-badge&labelColor=E5E7EB&color=00C49A)](https://github.com/microsoft/ai-agents-for-beginners?WT.mc_id=academic-105485-koreyst) --- -### Siri Generatif AI -[![Kecerdasan Buatan Generatif untuk Pemula](https://img.shields.io/badge/Generative%20AI%20for%20Beginners-8B5CF6?style=for-the-badge&labelColor=E5E7EB&color=8B5CF6)](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-105485-koreyst) -[![Kecerdasan Buatan Generatif (.NET)](https://img.shields.io/badge/Generative%20AI%20(.NET)-9333EA?style=for-the-badge&labelColor=E5E7EB&color=9333EA)](https://github.com/microsoft/Generative-AI-for-beginners-dotnet?WT.mc_id=academic-105485-koreyst) -[![Kecerdasan Buatan Generatif (Java)](https://img.shields.io/badge/Generative%20AI%20(Java)-C084FC?style=for-the-badge&labelColor=E5E7EB&color=C084FC)](https://github.com/microsoft/generative-ai-for-beginners-java?WT.mc_id=academic-105485-koreyst) -[![Kecerdasan Buatan Generatif (JavaScript)](https://img.shields.io/badge/Generative%20AI%20(JavaScript)-E879F9?style=for-the-badge&labelColor=E5E7EB&color=E879F9)](https://github.com/microsoft/generative-ai-with-javascript?WT.mc_id=academic-105485-koreyst) +### Siri AI Generatif +[![Generative AI for Beginners](https://img.shields.io/badge/Generative%20AI%20for%20Beginners-8B5CF6?style=for-the-badge&labelColor=E5E7EB&color=8B5CF6)](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-105485-koreyst) +[![Generative AI (.NET)](https://img.shields.io/badge/Generative%20AI%20(.NET)-9333EA?style=for-the-badge&labelColor=E5E7EB&color=9333EA)](https://github.com/microsoft/Generative-AI-for-beginners-dotnet?WT.mc_id=academic-105485-koreyst) +[![Generative AI (Java)](https://img.shields.io/badge/Generative%20AI%20(Java)-C084FC?style=for-the-badge&labelColor=E5E7EB&color=C084FC)](https://github.com/microsoft/generative-ai-for-beginners-java?WT.mc_id=academic-105485-koreyst) +[![Generative AI (JavaScript)](https://img.shields.io/badge/Generative%20AI%20(JavaScript)-E879F9?style=for-the-badge&labelColor=E5E7EB&color=E879F9)](https://github.com/microsoft/generative-ai-with-javascript?WT.mc_id=academic-105485-koreyst) --- ### Pembelajaran Teras -[![Pembelajaran Mesin untuk Pemula](https://img.shields.io/badge/ML%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=22C55E)](https://aka.ms/ml-beginners?WT.mc_id=academic-105485-koreyst) -[![Sains Data untuk Pemula](https://img.shields.io/badge/Data%20Science%20for%20Beginners-84CC16?style=for-the-badge&labelColor=E5E7EB&color=84CC16)](https://aka.ms/datascience-beginners?WT.mc_id=academic-105485-koreyst) -[![Kecerdasan Buatan untuk Pemula](https://img.shields.io/badge/AI%20for%20Beginners-A3E635?style=for-the-badge&labelColor=E5E7EB&color=A3E635)](https://aka.ms/ai-beginners?WT.mc_id=academic-105485-koreyst) -[![Keselamatan Siber untuk Pemula](https://img.shields.io/badge/Cybersecurity%20for%20Beginners-F97316?style=for-the-badge&labelColor=E5E7EB&color=F97316)](https://github.com/microsoft/Security-101?WT.mc_id=academic-96948-sayoung) -[![Pembangunan Web untuk Pemula](https://img.shields.io/badge/Web%20Dev%20for%20Beginners-EC4899?style=for-the-badge&labelColor=E5E7EB&color=EC4899)](https://aka.ms/webdev-beginners?WT.mc_id=academic-105485-koreyst) -[![IoT untuk Pemula](https://img.shields.io/badge/IoT%20for%20Beginners-14B8A6?style=for-the-badge&labelColor=E5E7EB&color=14B8A6)](https://aka.ms/iot-beginners?WT.mc_id=academic-105485-koreyst) -[![Pembangunan XR untuk Pemula](https://img.shields.io/badge/XR%20Development%20for%20Beginners-38BDF8?style=for-the-badge&labelColor=E5E7EB&color=38BDF8)](https://github.com/microsoft/xr-development-for-beginners?WT.mc_id=academic-105485-koreyst) +[![ML for Beginners](https://img.shields.io/badge/ML%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=22C55E)](https://aka.ms/ml-beginners?WT.mc_id=academic-105485-koreyst) +[![Data Science for Beginners](https://img.shields.io/badge/Data%20Science%20for%20Beginners-84CC16?style=for-the-badge&labelColor=E5E7EB&color=84CC16)](https://aka.ms/datascience-beginners?WT.mc_id=academic-105485-koreyst) +[![AI for Beginners](https://img.shields.io/badge/AI%20for%20Beginners-A3E635?style=for-the-badge&labelColor=E5E7EB&color=A3E635)](https://aka.ms/ai-beginners?WT.mc_id=academic-105485-koreyst) +[![Cybersecurity for Beginners](https://img.shields.io/badge/Cybersecurity%20for%20Beginners-F97316?style=for-the-badge&labelColor=E5E7EB&color=F97316)](https://github.com/microsoft/Security-101?WT.mc_id=academic-96948-sayoung) +[![Web Dev for Beginners](https://img.shields.io/badge/Web%20Dev%20for%20Beginners-EC4899?style=for-the-badge&labelColor=E5E7EB&color=EC4899)](https://aka.ms/webdev-beginners?WT.mc_id=academic-105485-koreyst) +[![IoT for Beginners](https://img.shields.io/badge/IoT%20for%20Beginners-14B8A6?style=for-the-badge&labelColor=E5E7EB&color=14B8A6)](https://aka.ms/iot-beginners?WT.mc_id=academic-105485-koreyst) +[![XR Development for Beginners](https://img.shields.io/badge/XR%20Development%20for%20Beginners-38BDF8?style=for-the-badge&labelColor=E5E7EB&color=38BDF8)](https://github.com/microsoft/xr-development-for-beginners?WT.mc_id=academic-105485-koreyst) --- ### Siri Copilot -[![Copilot untuk Pemrograman Berpasangan AI](https://img.shields.io/badge/Copilot%20for%20AI%20Paired%20Programming-FACC15?style=for-the-badge&labelColor=E5E7EB&color=FACC15)](https://aka.ms/GitHubCopilotAI?WT.mc_id=academic-105485-koreyst) -[![Copilot untuk C#/.NET](https://img.shields.io/badge/Copilot%20for%20C%23/.NET-FBBF24?style=for-the-badge&labelColor=E5E7EB&color=FBBF24)](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers?WT.mc_id=academic-105485-koreyst) -[![Pengembaraan Copilot](https://img.shields.io/badge/Copilot%20Adventure-FDE68A?style=for-the-badge&labelColor=E5E7EB&color=FDE68A)](https://github.com/microsoft/CopilotAdventures?WT.mc_id=academic-105485-koreyst) +[![Copilot for AI Paired Programming](https://img.shields.io/badge/Copilot%20for%20AI%20Paired%20Programming-FACC15?style=for-the-badge&labelColor=E5E7EB&color=FACC15)](https://aka.ms/GitHubCopilotAI?WT.mc_id=academic-105485-koreyst) +[![Copilot for C#/.NET](https://img.shields.io/badge/Copilot%20for%20C%23/.NET-FBBF24?style=for-the-badge&labelColor=E5E7EB&color=FBBF24)](https://github.com/microsoft/mastering-github-copilot-for-dotnet-csharp-developers?WT.mc_id=academic-105485-koreyst) +[![Copilot Adventure](https://img.shields.io/badge/Copilot%20Adventure-FDE68A?style=for-the-badge&labelColor=E5E7EB&color=FDE68A)](https://github.com/microsoft/CopilotAdventures?WT.mc_id=academic-105485-koreyst) ## Mendapatkan Bantuan -Jika anda tersekat atau mempunyai sebarang soalan mengenai membina aplikasi AI. Sertai pembelajar lain dan pembangun berpengalaman dalam perbincangan mengenai MCP. Ia adalah komuniti yang menyokong di mana soalan dialu-alukan dan pengetahuan dikongsi secara bebas. +Jika anda tersekat atau mempunyai sebarang soalan tentang membina aplikasi AI. Sertai pelajar lain dan pembangun berpengalaman dalam perbincangan mengenai MCP. Ia adalah komuniti yang menyokong di mana soalan dialu-alukan dan pengetahuan dikongsi secara bebas. [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -Jika anda mempunyai maklum balas produk atau menghadapi kesilapan ketika membina, kunjungi: +Jika anda mempunyai maklum balas produk atau ralat semasa membina, lawati: -[![Forum Pembangun Microsoft Foundry](https://img.shields.io/badge/GitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https://aka.ms/foundry/forum) +[![Microsoft Foundry Developer Forum](https://img.shields.io/badge/GitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https://aka.ms/foundry/forum) --- -**Penafian**: -Dokumen ini telah diterjemahkan menggunakan perkhidmatan terjemahan AI [Co-op Translator](https://github.com/Azure/co-op-translator). Walaupun kami berusaha untuk mencapai ketepatan, sila ambil perhatian bahawa terjemahan automatik mungkin mengandungi kesilapan atau ketidaktepatan. Dokumen asal dalam bahasa asalnya harus dianggap sebagai sumber yang sahih. Untuk maklumat penting, disarankan menggunakan terjemahan profesional oleh manusia. Kami tidak bertanggungjawab atas sebarang salah faham atau salah tafsir yang timbul daripada penggunaan terjemahan ini. +**Penafian**: +Dokumen ini telah diterjemahkan menggunakan perkhidmatan terjemahan AI [Co-op Translator](https://github.com/Azure/co-op-translator). Walaupun kami berusaha untuk ketepatan, sila ambil perhatian bahawa terjemahan automatik mungkin mengandungi kesilapan atau ketidaktepatan. Dokumen asal dalam bahasa asalnya harus dianggap sebagai sumber yang sah. Untuk maklumat penting, terjemahan profesional oleh insan adalah disyorkan. Kami tidak bertanggungjawab atas sebarang salah faham atau salah tafsir yang timbul daripada penggunaan terjemahan ini. \ No newline at end of file diff --git a/translations/ms/SECURITY.md b/translations/ms/SECURITY.md index 3d20591f6..af959f873 100644 --- a/translations/ms/SECURITY.md +++ b/translations/ms/SECURITY.md @@ -1,12 +1,3 @@ - ## Keselamatan Microsoft mengambil serius keselamatan produk dan perkhidmatan perisian kami, termasuk semua repositori kod sumber yang diuruskan melalui organisasi GitHub kami, yang merangkumi [Microsoft](https://github.com/Microsoft), [Azure](https://github.com/Azure), [DotNet](https://github.com/dotnet), [AspNet](https://github.com/aspnet), [Xamarin](https://github.com/xamarin), dan [organisasi GitHub kami](https://opensource.microsoft.com/). diff --git a/translations/ms/SUPPORT.md b/translations/ms/SUPPORT.md index 6afc40c80..494fade09 100644 --- a/translations/ms/SUPPORT.md +++ b/translations/ms/SUPPORT.md @@ -1,12 +1,3 @@ - # Sokongan ## Cara untuk melaporkan isu dan mendapatkan bantuan diff --git a/translations/ms/TROUBLESHOOTING.md b/translations/ms/TROUBLESHOOTING.md index 9a10c3e8d..c1684586a 100644 --- a/translations/ms/TROUBLESHOOTING.md +++ b/translations/ms/TROUBLESHOOTING.md @@ -1,12 +1,3 @@ - # Panduan Penyelesaian Masalah Panduan ini membantu anda menyelesaikan masalah biasa semasa menggunakan kurikulum Machine Learning for Beginners. Jika anda tidak menemui penyelesaian di sini, sila semak [Perbincangan Discord](https://aka.ms/foundry/discord) atau [buka isu](https://github.com/microsoft/ML-For-Beginners/issues). diff --git a/translations/ms/docs/_sidebar.md b/translations/ms/docs/_sidebar.md index 38b0d45c7..826887c56 100644 --- a/translations/ms/docs/_sidebar.md +++ b/translations/ms/docs/_sidebar.md @@ -1,12 +1,3 @@ - - Pengenalan - [Pengenalan kepada Pembelajaran Mesin](../1-Introduction/1-intro-to-ML/README.md) - [Sejarah Pembelajaran Mesin](../1-Introduction/2-history-of-ML/README.md) diff --git a/translations/ms/for-teachers.md b/translations/ms/for-teachers.md index 2887109db..7d4f564db 100644 --- a/translations/ms/for-teachers.md +++ b/translations/ms/for-teachers.md @@ -1,12 +1,3 @@ - ## Untuk Pendidik Adakah anda ingin menggunakan kurikulum ini di dalam kelas anda? Jangan ragu untuk mencubanya! diff --git a/translations/ms/quiz-app/README.md b/translations/ms/quiz-app/README.md index abdd2d8c9..649dd7fb9 100644 --- a/translations/ms/quiz-app/README.md +++ b/translations/ms/quiz-app/README.md @@ -1,12 +1,3 @@ - # Kuiz Kuiz-kuiz ini adalah kuiz sebelum dan selepas kuliah untuk kurikulum ML di https://aka.ms/ml-beginners diff --git a/translations/ms/sketchnotes/LICENSE.md b/translations/ms/sketchnotes/LICENSE.md index e002513c8..f0d8be100 100644 --- a/translations/ms/sketchnotes/LICENSE.md +++ b/translations/ms/sketchnotes/LICENSE.md @@ -1,12 +1,3 @@ - Hak Cipta Creative Commons Attribution-ShareAlike 4.0 Antarabangsa ======================================================================= diff --git a/translations/ms/sketchnotes/README.md b/translations/ms/sketchnotes/README.md index 0f2945622..3f0001b5f 100644 --- a/translations/ms/sketchnotes/README.md +++ b/translations/ms/sketchnotes/README.md @@ -1,12 +1,3 @@ - Semua sketchnote kurikulum boleh 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--git a/translations/tl/1-Introduction/1-intro-to-ML/README.md b/translations/tl/1-Introduction/1-intro-to-ML/README.md index 9bec14deb..00599a9a6 100644 --- a/translations/tl/1-Introduction/1-intro-to-ML/README.md +++ b/translations/tl/1-Introduction/1-intro-to-ML/README.md @@ -1,12 +1,3 @@ - # Panimula sa machine learning ## [Pre-lecture quiz](https://ff-quizzes.netlify.app/en/ml/) diff --git a/translations/tl/1-Introduction/1-intro-to-ML/assignment.md b/translations/tl/1-Introduction/1-intro-to-ML/assignment.md index 6a6c8e271..f08b946d8 100644 --- a/translations/tl/1-Introduction/1-intro-to-ML/assignment.md +++ b/translations/tl/1-Introduction/1-intro-to-ML/assignment.md @@ -1,12 +1,3 @@ - # Magsimula at Magpatakbo ## Mga Instruksyon diff --git a/translations/tl/1-Introduction/2-history-of-ML/README.md b/translations/tl/1-Introduction/2-history-of-ML/README.md index f0a0616da..ae4b29be3 100644 --- a/translations/tl/1-Introduction/2-history-of-ML/README.md +++ b/translations/tl/1-Introduction/2-history-of-ML/README.md @@ -1,12 +1,3 @@ - # Kasaysayan ng Machine Learning ![Buod ng Kasaysayan ng Machine Learning sa isang sketchnote](../../../../sketchnotes/ml-history.png) diff --git a/translations/tl/1-Introduction/2-history-of-ML/assignment.md b/translations/tl/1-Introduction/2-history-of-ML/assignment.md index 064a1a8fe..62b2951fb 100644 --- a/translations/tl/1-Introduction/2-history-of-ML/assignment.md +++ b/translations/tl/1-Introduction/2-history-of-ML/assignment.md @@ -1,12 +1,3 @@ - # Gumawa ng Timeline ## Mga Instruksyon diff --git a/translations/tl/1-Introduction/3-fairness/README.md b/translations/tl/1-Introduction/3-fairness/README.md index c76e0d242..1b16aa4bf 100644 --- a/translations/tl/1-Introduction/3-fairness/README.md +++ b/translations/tl/1-Introduction/3-fairness/README.md @@ -1,12 +1,3 @@ - # Paggawa ng Solusyon sa Machine Learning gamit ang Responsible AI ![Buod ng Responsible AI sa Machine Learning sa isang sketchnote](../../../../sketchnotes/ml-fairness.png) diff --git a/translations/tl/1-Introduction/3-fairness/assignment.md b/translations/tl/1-Introduction/3-fairness/assignment.md index 40c83338a..07789b762 100644 --- a/translations/tl/1-Introduction/3-fairness/assignment.md +++ b/translations/tl/1-Introduction/3-fairness/assignment.md @@ -1,12 +1,3 @@ - # Tuklasin ang Responsible AI Toolbox ## Mga Tagubilin diff --git a/translations/tl/1-Introduction/4-techniques-of-ML/README.md b/translations/tl/1-Introduction/4-techniques-of-ML/README.md index cfd9f8d1f..d7f5833e4 100644 --- a/translations/tl/1-Introduction/4-techniques-of-ML/README.md +++ b/translations/tl/1-Introduction/4-techniques-of-ML/README.md @@ -1,12 +1,3 @@ - # Mga Teknik ng Machine Learning Ang proseso ng pagbuo, paggamit, at pagpapanatili ng mga modelo ng machine learning at ang datos na ginagamit nito ay ibang-iba kumpara sa maraming iba pang mga workflow ng pag-develop. Sa araling ito, lilinawin natin ang proseso at ilalahad ang mga pangunahing teknik na kailangan mong malaman. Ikaw ay: diff --git a/translations/tl/1-Introduction/4-techniques-of-ML/assignment.md b/translations/tl/1-Introduction/4-techniques-of-ML/assignment.md index fe782268f..73a263d09 100644 --- a/translations/tl/1-Introduction/4-techniques-of-ML/assignment.md +++ b/translations/tl/1-Introduction/4-techniques-of-ML/assignment.md @@ -1,12 +1,3 @@ - # Mag-interbyu ng isang data scientist ## Mga Instruksyon diff --git a/translations/tl/1-Introduction/README.md b/translations/tl/1-Introduction/README.md index 820efbcc1..ea57f2f32 100644 --- a/translations/tl/1-Introduction/README.md +++ b/translations/tl/1-Introduction/README.md @@ -1,12 +1,3 @@ - # Panimula sa machine learning Sa seksyong ito ng kurikulum, ipapakilala sa iyo ang mga pangunahing konsepto na bumubuo sa larangan ng machine learning, kung ano ito, at matutunan ang tungkol sa kasaysayan nito at ang mga teknik na ginagamit ng mga mananaliksik upang magtrabaho dito. Tuklasin natin ang bagong mundo ng ML nang magkasama! diff --git a/translations/tl/2-Regression/1-Tools/README.md b/translations/tl/2-Regression/1-Tools/README.md index 494a576c4..b852160ec 100644 --- a/translations/tl/2-Regression/1-Tools/README.md +++ b/translations/tl/2-Regression/1-Tools/README.md @@ -1,12 +1,3 @@ - # Magsimula sa Python at Scikit-learn para sa mga regression model ![Buod ng mga regression sa isang sketchnote](../../../../sketchnotes/ml-regression.png) diff --git a/translations/tl/2-Regression/1-Tools/assignment.md b/translations/tl/2-Regression/1-Tools/assignment.md index 301e9ada9..5653a82ed 100644 --- a/translations/tl/2-Regression/1-Tools/assignment.md +++ b/translations/tl/2-Regression/1-Tools/assignment.md @@ -1,12 +1,3 @@ - # Regression gamit ang Scikit-learn ## Mga Instruksyon diff --git a/translations/tl/2-Regression/1-Tools/solution/Julia/README.md b/translations/tl/2-Regression/1-Tools/solution/Julia/README.md index 48e6a17c5..058052d32 100644 --- a/translations/tl/2-Regression/1-Tools/solution/Julia/README.md +++ b/translations/tl/2-Regression/1-Tools/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/2-Regression/2-Data/README.md b/translations/tl/2-Regression/2-Data/README.md index 1032684af..3788020b0 100644 --- a/translations/tl/2-Regression/2-Data/README.md +++ b/translations/tl/2-Regression/2-Data/README.md @@ -1,12 +1,3 @@ - # Bumuo ng regression model gamit ang Scikit-learn: ihanda at i-visualize ang data ![Infographic ng data visualization](../../../../2-Regression/2-Data/images/data-visualization.png) diff --git a/translations/tl/2-Regression/2-Data/assignment.md b/translations/tl/2-Regression/2-Data/assignment.md index f1e25c641..fb93e5027 100644 --- a/translations/tl/2-Regression/2-Data/assignment.md +++ b/translations/tl/2-Regression/2-Data/assignment.md @@ -1,12 +1,3 @@ - # Paggalugad sa mga Visualisasyon Mayroong iba't ibang mga library na magagamit para sa data visualization. Gumawa ng ilang mga visualisasyon gamit ang Pumpkin data sa araling ito gamit ang matplotlib at seaborn sa isang sample notebook. Aling mga library ang mas madaling gamitin? diff --git a/translations/tl/2-Regression/2-Data/solution/Julia/README.md b/translations/tl/2-Regression/2-Data/solution/Julia/README.md index abaf93fd9..eec993235 100644 --- a/translations/tl/2-Regression/2-Data/solution/Julia/README.md +++ b/translations/tl/2-Regression/2-Data/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/2-Regression/3-Linear/README.md b/translations/tl/2-Regression/3-Linear/README.md index 02adce2e7..7780f4a4b 100644 --- a/translations/tl/2-Regression/3-Linear/README.md +++ b/translations/tl/2-Regression/3-Linear/README.md @@ -1,12 +1,3 @@ - # Gumawa ng regression model gamit ang Scikit-learn: regression sa apat na paraan ![Linear vs polynomial regression infographic](../../../../2-Regression/3-Linear/images/linear-polynomial.png) @@ -114,11 +105,11 @@ Ngayon na nauunawaan mo ang math sa likod ng linear regression, gumawa tayo ng R Mula sa nakaraang aralin, marahil nakita mo na ang average na presyo para sa iba't ibang buwan ay ganito: -Average price by month +Average price by month Ipinapakita nito na maaaring may correlation, at maaari nating subukang sanayin ang linear regression model upang hulaan ang relasyon sa pagitan ng `Month` at `Price`, o sa pagitan ng `DayOfYear` at `Price`. Narito ang scatter plot na nagpapakita ng huling relasyon: -Scatter plot of Price vs. Day of Year +Scatter plot of Price vs. Day of Year Tingnan natin kung may correlation gamit ang `corr` function: @@ -137,7 +128,7 @@ for i,var in enumerate(new_pumpkins['Variety'].unique()): ax = df.plot.scatter('DayOfYear','Price',ax=ax,c=colors[i],label=var) ``` -Scatter plot of Price vs. Day of Year +Scatter plot of Price vs. Day of Year Ang ating pagsisiyasat ay nagpapahiwatig na ang variety ay may mas malaking epekto sa kabuuang presyo kaysa sa aktwal na petsa ng pagbebenta. Makikita natin ito gamit ang bar graph: @@ -145,7 +136,7 @@ Ang ating pagsisiyasat ay nagpapahiwatig na ang variety ay may mas malaking epek new_pumpkins.groupby('Variety')['Price'].mean().plot(kind='bar') ``` -Bar graph of price vs variety +Bar graph of price vs variety Tumutok muna tayo sa isang pumpkin variety, ang 'pie type', at tingnan kung anong epekto ang petsa sa presyo: @@ -153,7 +144,7 @@ Tumutok muna tayo sa isang pumpkin variety, ang 'pie type', at tingnan kung anon pie_pumpkins = new_pumpkins[new_pumpkins['Variety']=='PIE TYPE'] pie_pumpkins.plot.scatter('DayOfYear','Price') ``` -Scatter plot of Price vs. Day of Year +Scatter plot of Price vs. Day of Year Kung kalkulahin natin ngayon ang correlation sa pagitan ng `Price` at `DayOfYear` gamit ang `corr` function, makakakuha tayo ng humigit-kumulang `-0.27` - na nangangahulugang may saysay ang pagsasanay ng predictive model. @@ -227,7 +218,7 @@ plt.scatter(X_test,y_test) plt.plot(X_test,pred) ``` -Linear regression +Linear regression ## Polynomial Regression @@ -256,7 +247,7 @@ Ang paggamit ng `PolynomialFeatures(2)` ay nangangahulugan na isasama natin ang Ang mga pipeline ay maaaring gamitin sa parehong paraan tulad ng orihinal na `LinearRegression` object, ibig sabihin maaari nating `fit` ang pipeline, at pagkatapos ay gamitin ang `predict` upang makuha ang mga resulta ng prediksyon. Narito ang graph na nagpapakita ng test data, at ang approximation curve: -Polynomial regression +Polynomial regression Sa paggamit ng Polynomial Regression, maaari tayong makakuha ng bahagyang mas mababang MSE at mas mataas na determination, ngunit hindi gaanong malaki. Kailangan nating isaalang-alang ang iba pang mga features! @@ -274,7 +265,7 @@ Sa ideal na mundo, nais nating mahulaan ang mga presyo para sa iba't ibang uri n Narito makikita mo kung paano nakadepende ang average na presyo sa variety: -Average price by variety +Average price by variety Upang isama ang variety, kailangan muna nating i-convert ito sa numeric form, o **encode** ito. May ilang paraan upang gawin ito: diff --git a/translations/tl/2-Regression/3-Linear/assignment.md b/translations/tl/2-Regression/3-Linear/assignment.md index 4f66c2b26..b33944cf8 100644 --- a/translations/tl/2-Regression/3-Linear/assignment.md +++ b/translations/tl/2-Regression/3-Linear/assignment.md @@ -1,12 +1,3 @@ - # Gumawa ng Regression Model ## Mga Instruksyon diff --git a/translations/tl/2-Regression/3-Linear/solution/Julia/README.md b/translations/tl/2-Regression/3-Linear/solution/Julia/README.md index 58ac29095..058052d32 100644 --- a/translations/tl/2-Regression/3-Linear/solution/Julia/README.md +++ b/translations/tl/2-Regression/3-Linear/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/2-Regression/4-Logistic/README.md b/translations/tl/2-Regression/4-Logistic/README.md index e87a90f67..fa3335b08 100644 --- a/translations/tl/2-Regression/4-Logistic/README.md +++ b/translations/tl/2-Regression/4-Logistic/README.md @@ -1,12 +1,3 @@ - # Logistic regression para sa pag-predict ng mga kategorya ![Infographic ng Logistic vs. Linear Regression](../../../../2-Regression/4-Logistic/images/linear-vs-logistic.png) diff --git a/translations/tl/2-Regression/4-Logistic/assignment.md b/translations/tl/2-Regression/4-Logistic/assignment.md index 94e384221..77ec28f7f 100644 --- a/translations/tl/2-Regression/4-Logistic/assignment.md +++ b/translations/tl/2-Regression/4-Logistic/assignment.md @@ -1,12 +1,3 @@ - # Pagsubok Muli ng Regression ## Mga Instruksyon diff --git a/translations/tl/2-Regression/4-Logistic/solution/Julia/README.md b/translations/tl/2-Regression/4-Logistic/solution/Julia/README.md index 3cd6aeda5..59b31b4ed 100644 --- a/translations/tl/2-Regression/4-Logistic/solution/Julia/README.md +++ b/translations/tl/2-Regression/4-Logistic/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/2-Regression/README.md b/translations/tl/2-Regression/README.md index c7db05249..3ca22c1ce 100644 --- a/translations/tl/2-Regression/README.md +++ b/translations/tl/2-Regression/README.md @@ -1,12 +1,3 @@ - # Mga Modelong Regression para sa Machine Learning ## Paksang Rehiyonal: Mga Modelong Regression para sa Presyo ng Kalabasa sa Hilagang Amerika 🎃 diff --git a/translations/tl/3-Web-App/1-Web-App/README.md b/translations/tl/3-Web-App/1-Web-App/README.md index 6872280b4..d60220b11 100644 --- a/translations/tl/3-Web-App/1-Web-App/README.md +++ b/translations/tl/3-Web-App/1-Web-App/README.md @@ -1,12 +1,3 @@ - # Gumawa ng Web App para Gamitin ang ML Model Sa araling ito, magtetrain ka ng ML model gamit ang isang data set na kakaiba: _mga sightings ng UFO sa nakaraang siglo_, na galing sa database ng NUFORC. diff --git a/translations/tl/3-Web-App/1-Web-App/assignment.md b/translations/tl/3-Web-App/1-Web-App/assignment.md index fdb835644..e66e743b1 100644 --- a/translations/tl/3-Web-App/1-Web-App/assignment.md +++ b/translations/tl/3-Web-App/1-Web-App/assignment.md @@ -1,12 +1,3 @@ - # Subukan ang ibang modelo ## Mga Instruksyon diff --git a/translations/tl/3-Web-App/README.md b/translations/tl/3-Web-App/README.md index e5802ce4b..397532ee4 100644 --- a/translations/tl/3-Web-App/README.md +++ b/translations/tl/3-Web-App/README.md @@ -1,12 +1,3 @@ - # Gumawa ng web app para magamit ang iyong ML model Sa seksyong ito ng kurikulum, ipapakilala sa iyo ang isang praktikal na paksa sa ML: kung paano i-save ang iyong Scikit-learn model bilang isang file na magagamit para gumawa ng mga prediksyon sa loob ng isang web application. Kapag na-save na ang model, matutunan mo kung paano ito gamitin sa isang web app na ginawa gamit ang Flask. Una, gagawa ka ng model gamit ang ilang data na may kaugnayan sa mga sightings ng UFO! Pagkatapos, gagawa ka ng isang web app na magbibigay-daan sa iyo na mag-input ng bilang ng mga segundo kasama ang latitude at longitude value upang hulaan kung aling bansa ang nag-ulat ng pag-sighting ng UFO. diff --git a/translations/tl/4-Classification/1-Introduction/README.md b/translations/tl/4-Classification/1-Introduction/README.md index bfe31d3f5..2ec1a31c7 100644 --- a/translations/tl/4-Classification/1-Introduction/README.md +++ b/translations/tl/4-Classification/1-Introduction/README.md @@ -1,12 +1,3 @@ - # Panimula sa klasipikasyon Sa apat na araling ito, iyong matutuklasan ang isang mahalagang aspeto ng klasikong machine learning - _klasipikasyon_. Tatalakayin natin ang paggamit ng iba't ibang klasipikasyon na algorithm gamit ang dataset tungkol sa mga kahanga-hangang lutuin ng Asya at India. Sana'y gutom ka na! diff --git a/translations/tl/4-Classification/1-Introduction/assignment.md b/translations/tl/4-Classification/1-Introduction/assignment.md index f63389d16..bc3b2fadb 100644 --- a/translations/tl/4-Classification/1-Introduction/assignment.md +++ b/translations/tl/4-Classification/1-Introduction/assignment.md @@ -1,12 +1,3 @@ - # Tuklasin ang mga pamamaraan ng klasipikasyon ## Mga Instruksyon diff --git a/translations/tl/4-Classification/1-Introduction/solution/Julia/README.md b/translations/tl/4-Classification/1-Introduction/solution/Julia/README.md index 0a28c92b5..59b31b4ed 100644 --- a/translations/tl/4-Classification/1-Introduction/solution/Julia/README.md +++ b/translations/tl/4-Classification/1-Introduction/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/4-Classification/2-Classifiers-1/README.md b/translations/tl/4-Classification/2-Classifiers-1/README.md index c895be8b5..605897c3b 100644 --- a/translations/tl/4-Classification/2-Classifiers-1/README.md +++ b/translations/tl/4-Classification/2-Classifiers-1/README.md @@ -1,12 +1,3 @@ - # Mga Classifier ng Lutuin 1 Sa araling ito, gagamitin mo ang dataset na na-save mo mula sa nakaraang aralin na puno ng balanseng, malinis na datos tungkol sa mga lutuin. diff --git a/translations/tl/4-Classification/2-Classifiers-1/assignment.md b/translations/tl/4-Classification/2-Classifiers-1/assignment.md index 1f638adbd..3873fbdbc 100644 --- a/translations/tl/4-Classification/2-Classifiers-1/assignment.md +++ b/translations/tl/4-Classification/2-Classifiers-1/assignment.md @@ -1,12 +1,3 @@ - # Pag-aralan ang mga solvers ## Mga Instruksyon diff --git a/translations/tl/4-Classification/2-Classifiers-1/solution/Julia/README.md b/translations/tl/4-Classification/2-Classifiers-1/solution/Julia/README.md index bc9e6e526..058052d32 100644 --- a/translations/tl/4-Classification/2-Classifiers-1/solution/Julia/README.md +++ b/translations/tl/4-Classification/2-Classifiers-1/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/4-Classification/3-Classifiers-2/README.md b/translations/tl/4-Classification/3-Classifiers-2/README.md index 5537fd3a9..ab48568d5 100644 --- a/translations/tl/4-Classification/3-Classifiers-2/README.md +++ b/translations/tl/4-Classification/3-Classifiers-2/README.md @@ -1,12 +1,3 @@ - # Mga Classifier ng Lutuin 2 Sa ikalawang aralin ng klasipikasyon na ito, mas marami kang matutuklasang paraan upang iklasipika ang numerikong datos. Malalaman mo rin ang mga epekto ng pagpili ng isang classifier kumpara sa iba. diff --git a/translations/tl/4-Classification/3-Classifiers-2/assignment.md b/translations/tl/4-Classification/3-Classifiers-2/assignment.md index 530db6899..12b0c1c9c 100644 --- a/translations/tl/4-Classification/3-Classifiers-2/assignment.md +++ b/translations/tl/4-Classification/3-Classifiers-2/assignment.md @@ -1,12 +1,3 @@ - # Paglalaro sa Parameter ## Mga Instruksyon diff --git a/translations/tl/4-Classification/3-Classifiers-2/solution/Julia/README.md b/translations/tl/4-Classification/3-Classifiers-2/solution/Julia/README.md index 90ac1c5ad..59b31b4ed 100644 --- a/translations/tl/4-Classification/3-Classifiers-2/solution/Julia/README.md +++ b/translations/tl/4-Classification/3-Classifiers-2/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/4-Classification/4-Applied/README.md b/translations/tl/4-Classification/4-Applied/README.md index b48c56c68..c3f8bf5ad 100644 --- a/translations/tl/4-Classification/4-Applied/README.md +++ b/translations/tl/4-Classification/4-Applied/README.md @@ -1,12 +1,3 @@ - # Gumawa ng Web App para sa Pagrekomenda ng Lutuin Sa araling ito, gagawa ka ng isang classification model gamit ang ilan sa mga teknik na natutunan mo sa mga nakaraang aralin, gamit ang masarap na dataset ng lutuin na ginamit sa buong serye. Bukod dito, gagawa ka ng isang maliit na web app upang magamit ang naka-save na model, gamit ang web runtime ng Onnx. diff --git a/translations/tl/4-Classification/4-Applied/assignment.md b/translations/tl/4-Classification/4-Applied/assignment.md index 55b30f783..0035d695b 100644 --- a/translations/tl/4-Classification/4-Applied/assignment.md +++ b/translations/tl/4-Classification/4-Applied/assignment.md @@ -1,12 +1,3 @@ - # Gumawa ng Recommender ## Mga Instruksyon diff --git a/translations/tl/4-Classification/README.md b/translations/tl/4-Classification/README.md index 6f92ad658..393f76ea2 100644 --- a/translations/tl/4-Classification/README.md +++ b/translations/tl/4-Classification/README.md @@ -1,12 +1,3 @@ - # Pagsisimula sa klasipikasyon ## Paksang Rehiyonal: Masasarap na Lutuing Asyano at Indian 🍜 diff --git a/translations/tl/5-Clustering/1-Visualize/README.md b/translations/tl/5-Clustering/1-Visualize/README.md index 395721f5d..6d74109ba 100644 --- a/translations/tl/5-Clustering/1-Visualize/README.md +++ b/translations/tl/5-Clustering/1-Visualize/README.md @@ -1,12 +1,3 @@ - # Panimula sa clustering Ang clustering ay isang uri ng [Unsupervised Learning](https://wikipedia.org/wiki/Unsupervised_learning) na ipinapalagay na ang dataset ay walang label o ang mga input nito ay hindi tumutugma sa mga pre-defined na output. Gumagamit ito ng iba't ibang algorithm upang suriin ang unlabeled na data at magbigay ng mga pangkat batay sa mga pattern na natutuklasan nito sa data. diff --git a/translations/tl/5-Clustering/1-Visualize/assignment.md b/translations/tl/5-Clustering/1-Visualize/assignment.md index 3d34e35db..b5f3d7ec7 100644 --- a/translations/tl/5-Clustering/1-Visualize/assignment.md +++ b/translations/tl/5-Clustering/1-Visualize/assignment.md @@ -1,12 +1,3 @@ - # Mag-research ng iba pang visualizations para sa clustering ## Mga Instruksyon diff --git a/translations/tl/5-Clustering/1-Visualize/solution/Julia/README.md b/translations/tl/5-Clustering/1-Visualize/solution/Julia/README.md index 035a32d0a..058052d32 100644 --- a/translations/tl/5-Clustering/1-Visualize/solution/Julia/README.md +++ b/translations/tl/5-Clustering/1-Visualize/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/5-Clustering/2-K-Means/README.md b/translations/tl/5-Clustering/2-K-Means/README.md index c9f7fd265..697d23032 100644 --- a/translations/tl/5-Clustering/2-K-Means/README.md +++ b/translations/tl/5-Clustering/2-K-Means/README.md @@ -1,12 +1,3 @@ - # K-Means clustering ## [Pre-lecture quiz](https://ff-quizzes.netlify.app/en/ml/) diff --git a/translations/tl/5-Clustering/2-K-Means/assignment.md b/translations/tl/5-Clustering/2-K-Means/assignment.md index 0804e2b8a..806f0806a 100644 --- a/translations/tl/5-Clustering/2-K-Means/assignment.md +++ b/translations/tl/5-Clustering/2-K-Means/assignment.md @@ -1,12 +1,3 @@ - # Subukan ang iba't ibang paraan ng clustering ## Mga Instruksyon diff --git a/translations/tl/5-Clustering/2-K-Means/solution/Julia/README.md b/translations/tl/5-Clustering/2-K-Means/solution/Julia/README.md index 5d694eee7..058052d32 100644 --- a/translations/tl/5-Clustering/2-K-Means/solution/Julia/README.md +++ b/translations/tl/5-Clustering/2-K-Means/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/5-Clustering/README.md b/translations/tl/5-Clustering/README.md index 9d5c322b8..4f2f2a63d 100644 --- a/translations/tl/5-Clustering/README.md +++ b/translations/tl/5-Clustering/README.md @@ -1,12 +1,3 @@ - # Mga modelo ng clustering para sa machine learning Ang clustering ay isang gawain sa machine learning kung saan sinusubukan nitong hanapin ang mga bagay na magkahawig at pagsama-samahin ang mga ito sa mga grupo na tinatawag na clusters. Ang kaibahan ng clustering sa ibang mga pamamaraan sa machine learning ay nangyayari ito nang awtomatiko. Sa katunayan, maituturing na ito ang kabaligtaran ng supervised learning. diff --git a/translations/tl/6-NLP/1-Introduction-to-NLP/README.md b/translations/tl/6-NLP/1-Introduction-to-NLP/README.md index 6c3ed247e..cc948b1fc 100644 --- a/translations/tl/6-NLP/1-Introduction-to-NLP/README.md +++ b/translations/tl/6-NLP/1-Introduction-to-NLP/README.md @@ -1,12 +1,3 @@ - # Panimula sa natural language processing Ang araling ito ay tumatalakay sa maikling kasaysayan at mahahalagang konsepto ng *natural language processing*, isang subfield ng *computational linguistics*. diff --git a/translations/tl/6-NLP/1-Introduction-to-NLP/assignment.md b/translations/tl/6-NLP/1-Introduction-to-NLP/assignment.md index f148f4c4f..1ad79ffeb 100644 --- a/translations/tl/6-NLP/1-Introduction-to-NLP/assignment.md +++ b/translations/tl/6-NLP/1-Introduction-to-NLP/assignment.md @@ -1,12 +1,3 @@ - # Maghanap ng Bot ## Mga Tagubilin diff --git a/translations/tl/6-NLP/2-Tasks/README.md b/translations/tl/6-NLP/2-Tasks/README.md index 535b5b505..05b79c8a9 100644 --- a/translations/tl/6-NLP/2-Tasks/README.md +++ b/translations/tl/6-NLP/2-Tasks/README.md @@ -1,12 +1,3 @@ - # Karaniwang mga gawain at teknika sa natural language processing Para sa karamihan ng mga gawain sa *natural language processing*, ang teksto na kailangang iproseso ay kailangang hatiin, suriin, at ang mga resulta ay itabi o i-cross reference gamit ang mga patakaran at data set. Ang mga gawaing ito ay nagbibigay-daan sa programmer na matukoy ang _kahulugan_, _layunin_, o kahit ang _dalas_ ng mga termino at salita sa isang teksto. diff --git a/translations/tl/6-NLP/2-Tasks/assignment.md b/translations/tl/6-NLP/2-Tasks/assignment.md index 00053bace..f34ac5fa8 100644 --- a/translations/tl/6-NLP/2-Tasks/assignment.md +++ b/translations/tl/6-NLP/2-Tasks/assignment.md @@ -1,12 +1,3 @@ - # Paano Magpausap ng Bot ## Mga Instruksyon diff --git a/translations/tl/6-NLP/3-Translation-Sentiment/README.md b/translations/tl/6-NLP/3-Translation-Sentiment/README.md index 30cd5ff8a..ec0017435 100644 --- a/translations/tl/6-NLP/3-Translation-Sentiment/README.md +++ b/translations/tl/6-NLP/3-Translation-Sentiment/README.md @@ -1,12 +1,3 @@ - # Pagsasalin at Sentiment Analysis gamit ang ML Sa mga nakaraang aralin, natutunan mo kung paano bumuo ng isang simpleng bot gamit ang `TextBlob`, isang library na gumagamit ng ML sa likod ng eksena upang magsagawa ng mga pangunahing gawain sa NLP tulad ng pagkuha ng mga parirala ng pangngalan. Isa pang mahalagang hamon sa computational linguistics ay ang tumpak na _pagsasalin_ ng isang pangungusap mula sa isang sinasalita o nakasulat na wika patungo sa isa pa. diff --git a/translations/tl/6-NLP/3-Translation-Sentiment/assignment.md b/translations/tl/6-NLP/3-Translation-Sentiment/assignment.md index 0b3176186..f5c1064fe 100644 --- a/translations/tl/6-NLP/3-Translation-Sentiment/assignment.md +++ b/translations/tl/6-NLP/3-Translation-Sentiment/assignment.md @@ -1,12 +1,3 @@ - # Lisensyang Pampanitikan ## Mga Panuto diff --git a/translations/tl/6-NLP/3-Translation-Sentiment/solution/Julia/README.md b/translations/tl/6-NLP/3-Translation-Sentiment/solution/Julia/README.md index 1a2de5b97..058052d32 100644 --- a/translations/tl/6-NLP/3-Translation-Sentiment/solution/Julia/README.md +++ b/translations/tl/6-NLP/3-Translation-Sentiment/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/6-NLP/3-Translation-Sentiment/solution/R/README.md b/translations/tl/6-NLP/3-Translation-Sentiment/solution/R/README.md index 3153017ca..59b31b4ed 100644 --- a/translations/tl/6-NLP/3-Translation-Sentiment/solution/R/README.md +++ b/translations/tl/6-NLP/3-Translation-Sentiment/solution/R/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/6-NLP/4-Hotel-Reviews-1/README.md b/translations/tl/6-NLP/4-Hotel-Reviews-1/README.md index 80ecd1357..f535ac2fe 100644 --- a/translations/tl/6-NLP/4-Hotel-Reviews-1/README.md +++ b/translations/tl/6-NLP/4-Hotel-Reviews-1/README.md @@ -1,12 +1,3 @@ - # Sentiment analysis gamit ang mga review ng hotel - pagproseso ng data Sa seksyong ito, gagamitin mo ang mga teknik na natutunan sa mga nakaraang aralin upang magsagawa ng exploratory data analysis sa isang malaking dataset. Kapag nagkaroon ka ng mas malalim na pag-unawa sa kahalagahan ng iba't ibang column, matutunan mo: diff --git a/translations/tl/6-NLP/4-Hotel-Reviews-1/assignment.md b/translations/tl/6-NLP/4-Hotel-Reviews-1/assignment.md index 5752520ea..7d05817b1 100644 --- a/translations/tl/6-NLP/4-Hotel-Reviews-1/assignment.md +++ b/translations/tl/6-NLP/4-Hotel-Reviews-1/assignment.md @@ -1,12 +1,3 @@ - # NLTK ## Mga Panuto diff --git a/translations/tl/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md b/translations/tl/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md index 131e5b4d1..59b31b4ed 100644 --- a/translations/tl/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md +++ b/translations/tl/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/6-NLP/4-Hotel-Reviews-1/solution/R/README.md b/translations/tl/6-NLP/4-Hotel-Reviews-1/solution/R/README.md index 1021de5e2..59b31b4ed 100644 --- a/translations/tl/6-NLP/4-Hotel-Reviews-1/solution/R/README.md +++ b/translations/tl/6-NLP/4-Hotel-Reviews-1/solution/R/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/6-NLP/5-Hotel-Reviews-2/README.md b/translations/tl/6-NLP/5-Hotel-Reviews-2/README.md index 91f9a071c..d2c58296d 100644 --- a/translations/tl/6-NLP/5-Hotel-Reviews-2/README.md +++ b/translations/tl/6-NLP/5-Hotel-Reviews-2/README.md @@ -1,12 +1,3 @@ - # Sentiment analysis gamit ang mga review ng hotel Ngayon na napag-aralan mo nang mabuti ang dataset, oras na para i-filter ang mga column at gamitin ang mga teknik ng NLP sa dataset upang makakuha ng mga bagong insight tungkol sa mga hotel. diff --git a/translations/tl/6-NLP/5-Hotel-Reviews-2/assignment.md b/translations/tl/6-NLP/5-Hotel-Reviews-2/assignment.md index 1e137de87..227cc98a1 100644 --- a/translations/tl/6-NLP/5-Hotel-Reviews-2/assignment.md +++ b/translations/tl/6-NLP/5-Hotel-Reviews-2/assignment.md @@ -1,12 +1,3 @@ - # Subukan ang ibang dataset ## Mga Instruksyon diff --git a/translations/tl/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md b/translations/tl/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md index d90020045..058052d32 100644 --- a/translations/tl/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md +++ b/translations/tl/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/6-NLP/5-Hotel-Reviews-2/solution/R/README.md b/translations/tl/6-NLP/5-Hotel-Reviews-2/solution/R/README.md index d4817034a..058052d32 100644 --- a/translations/tl/6-NLP/5-Hotel-Reviews-2/solution/R/README.md +++ b/translations/tl/6-NLP/5-Hotel-Reviews-2/solution/R/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/6-NLP/README.md b/translations/tl/6-NLP/README.md index c3e0076a7..567e1886b 100644 --- a/translations/tl/6-NLP/README.md +++ b/translations/tl/6-NLP/README.md @@ -1,12 +1,3 @@ - # Pagsisimula sa natural language processing Ang natural language processing (NLP) ay ang kakayahan ng isang programa sa computer na maunawaan ang wika ng tao, kung paano ito sinasalita at isinusulat -- tinatawag na natural na wika. Isa itong bahagi ng artificial intelligence (AI). Ang NLP ay umiiral na nang mahigit 50 taon at may mga ugat sa larangan ng lingguwistika. Ang buong larangan ay nakatuon sa pagtulong sa mga makina na maunawaan at maproseso ang wika ng tao. Maaari itong magamit upang maisagawa ang mga gawain tulad ng spell check o machine translation. Mayroon itong iba't ibang aplikasyon sa totoong mundo sa maraming larangan, kabilang ang pananaliksang medikal, mga search engine, at business intelligence. diff --git a/translations/tl/6-NLP/data/README.md b/translations/tl/6-NLP/data/README.md index 94a51184a..bb8397400 100644 --- a/translations/tl/6-NLP/data/README.md +++ b/translations/tl/6-NLP/data/README.md @@ -1,12 +1,3 @@ - I-download ang data ng pagsusuri sa hotel sa folder na ito. --- diff --git a/translations/tl/7-TimeSeries/1-Introduction/README.md b/translations/tl/7-TimeSeries/1-Introduction/README.md index ecab5b778..31560fa24 100644 --- a/translations/tl/7-TimeSeries/1-Introduction/README.md +++ b/translations/tl/7-TimeSeries/1-Introduction/README.md @@ -1,12 +1,3 @@ - # Panimula sa Pagtataya ng Time Series ![Buod ng time series sa isang sketchnote](../../../../sketchnotes/ml-timeseries.png) diff --git a/translations/tl/7-TimeSeries/1-Introduction/assignment.md b/translations/tl/7-TimeSeries/1-Introduction/assignment.md index c6f03d0d1..838d7e0dc 100644 --- a/translations/tl/7-TimeSeries/1-Introduction/assignment.md +++ b/translations/tl/7-TimeSeries/1-Introduction/assignment.md @@ -1,12 +1,3 @@ - # Mag-visualize ng Iba Pang Time Series ## Mga Instruksyon diff --git a/translations/tl/7-TimeSeries/1-Introduction/solution/Julia/README.md b/translations/tl/7-TimeSeries/1-Introduction/solution/Julia/README.md index 11efec7a6..eec993235 100644 --- a/translations/tl/7-TimeSeries/1-Introduction/solution/Julia/README.md +++ b/translations/tl/7-TimeSeries/1-Introduction/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/7-TimeSeries/1-Introduction/solution/R/README.md b/translations/tl/7-TimeSeries/1-Introduction/solution/R/README.md index 956a6518d..058052d32 100644 --- a/translations/tl/7-TimeSeries/1-Introduction/solution/R/README.md +++ b/translations/tl/7-TimeSeries/1-Introduction/solution/R/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/7-TimeSeries/2-ARIMA/README.md b/translations/tl/7-TimeSeries/2-ARIMA/README.md index ae425bc78..065a3731e 100644 --- a/translations/tl/7-TimeSeries/2-ARIMA/README.md +++ b/translations/tl/7-TimeSeries/2-ARIMA/README.md @@ -1,12 +1,3 @@ - # Time series forecasting gamit ang ARIMA Sa nakaraang aralin, natutunan mo ang tungkol sa time series forecasting at nag-load ng dataset na nagpapakita ng pagbabago-bago ng electrical load sa loob ng isang panahon. diff --git a/translations/tl/7-TimeSeries/2-ARIMA/assignment.md b/translations/tl/7-TimeSeries/2-ARIMA/assignment.md index 851ddece9..d9224211c 100644 --- a/translations/tl/7-TimeSeries/2-ARIMA/assignment.md +++ b/translations/tl/7-TimeSeries/2-ARIMA/assignment.md @@ -1,12 +1,3 @@ - # Isang bagong ARIMA model ## Mga Instruksyon diff --git a/translations/tl/7-TimeSeries/2-ARIMA/solution/Julia/README.md b/translations/tl/7-TimeSeries/2-ARIMA/solution/Julia/README.md index f308eabbf..058052d32 100644 --- a/translations/tl/7-TimeSeries/2-ARIMA/solution/Julia/README.md +++ b/translations/tl/7-TimeSeries/2-ARIMA/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/7-TimeSeries/2-ARIMA/solution/R/README.md b/translations/tl/7-TimeSeries/2-ARIMA/solution/R/README.md index 7a423786a..058052d32 100644 --- a/translations/tl/7-TimeSeries/2-ARIMA/solution/R/README.md +++ b/translations/tl/7-TimeSeries/2-ARIMA/solution/R/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/7-TimeSeries/3-SVR/README.md b/translations/tl/7-TimeSeries/3-SVR/README.md index 8371af082..11064254b 100644 --- a/translations/tl/7-TimeSeries/3-SVR/README.md +++ b/translations/tl/7-TimeSeries/3-SVR/README.md @@ -1,12 +1,3 @@ - # Pagtataya ng Time Series gamit ang Support Vector Regressor Sa nakaraang aralin, natutunan mo kung paano gamitin ang ARIMA model para gumawa ng mga prediksyon sa time series. Ngayon, titingnan natin ang Support Vector Regressor model, isang regressor model na ginagamit para magpredikta ng tuloy-tuloy na data. diff --git a/translations/tl/7-TimeSeries/3-SVR/assignment.md b/translations/tl/7-TimeSeries/3-SVR/assignment.md index 8e9f25f6b..c25c8ce08 100644 --- a/translations/tl/7-TimeSeries/3-SVR/assignment.md +++ b/translations/tl/7-TimeSeries/3-SVR/assignment.md @@ -1,12 +1,3 @@ - # Isang bagong modelo ng SVR ## Mga Instruksyon [^1] diff --git a/translations/tl/7-TimeSeries/README.md b/translations/tl/7-TimeSeries/README.md index d94714a6e..75ada10f5 100644 --- a/translations/tl/7-TimeSeries/README.md +++ b/translations/tl/7-TimeSeries/README.md @@ -1,12 +1,3 @@ - # Panimula sa pag-forecast ng time series Ano ang pag-forecast ng time series? Ito ay tungkol sa pag-predict ng mga darating na pangyayari sa pamamagitan ng pagsusuri ng mga trend sa nakaraan. diff --git a/translations/tl/8-Reinforcement/1-QLearning/README.md b/translations/tl/8-Reinforcement/1-QLearning/README.md index e641117fe..ccd3f1b49 100644 --- a/translations/tl/8-Reinforcement/1-QLearning/README.md +++ b/translations/tl/8-Reinforcement/1-QLearning/README.md @@ -1,12 +1,3 @@ - # Panimula sa Reinforcement Learning at Q-Learning ![Buod ng reinforcement sa machine learning sa isang sketchnote](../../../../sketchnotes/ml-reinforcement.png) diff --git a/translations/tl/8-Reinforcement/1-QLearning/assignment.md b/translations/tl/8-Reinforcement/1-QLearning/assignment.md index 4562770f7..903948f53 100644 --- a/translations/tl/8-Reinforcement/1-QLearning/assignment.md +++ b/translations/tl/8-Reinforcement/1-QLearning/assignment.md @@ -1,12 +1,3 @@ - # Isang Mas Realistikong Mundo Sa ating sitwasyon, halos hindi napapagod o nagugutom si Peter habang gumagalaw. Sa isang mas realistikong mundo, kailangan niyang umupo at magpahinga paminsan-minsan, at kailangan din niyang kumain. Gawin natin ang ating mundo na mas makatotohanan sa pamamagitan ng pagpapatupad ng mga sumusunod na patakaran: diff --git a/translations/tl/8-Reinforcement/1-QLearning/solution/Julia/README.md b/translations/tl/8-Reinforcement/1-QLearning/solution/Julia/README.md index 626702ced..058052d32 100644 --- a/translations/tl/8-Reinforcement/1-QLearning/solution/Julia/README.md +++ b/translations/tl/8-Reinforcement/1-QLearning/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/8-Reinforcement/1-QLearning/solution/R/README.md b/translations/tl/8-Reinforcement/1-QLearning/solution/R/README.md index 453ba9d2c..59b31b4ed 100644 --- a/translations/tl/8-Reinforcement/1-QLearning/solution/R/README.md +++ b/translations/tl/8-Reinforcement/1-QLearning/solution/R/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/8-Reinforcement/2-Gym/README.md b/translations/tl/8-Reinforcement/2-Gym/README.md index 79cc4495d..63c41202b 100644 --- a/translations/tl/8-Reinforcement/2-Gym/README.md +++ b/translations/tl/8-Reinforcement/2-Gym/README.md @@ -1,12 +1,3 @@ - ## Mga Paunang Kaalaman Sa araling ito, gagamit tayo ng library na tinatawag na **OpenAI Gym** upang mag-simulate ng iba't ibang **kapaligiran**. Maaari mong patakbuhin ang code ng araling ito nang lokal (halimbawa, mula sa Visual Studio Code), kung saan magbubukas ang simulation sa isang bagong window. Kapag pinapatakbo ang code online, maaaring kailanganin mong gumawa ng ilang pagbabago sa code, tulad ng inilarawan [dito](https://towardsdatascience.com/rendering-openai-gym-envs-on-binder-and-google-colab-536f99391cc7). diff --git a/translations/tl/8-Reinforcement/2-Gym/assignment.md b/translations/tl/8-Reinforcement/2-Gym/assignment.md index 3f97afa6e..07125b84d 100644 --- a/translations/tl/8-Reinforcement/2-Gym/assignment.md +++ b/translations/tl/8-Reinforcement/2-Gym/assignment.md @@ -1,12 +1,3 @@ - # Sanayin ang Mountain Car Ang [OpenAI Gym](http://gym.openai.com) ay dinisenyo sa paraang lahat ng mga environment ay may parehong API - ibig sabihin, pareho ang mga method na `reset`, `step`, at `render`, at pareho rin ang mga abstraction ng **action space** at **observation space**. Dahil dito, posible na i-adapt ang parehong reinforcement learning algorithms sa iba't ibang environment na may kaunting pagbabago sa code. diff --git a/translations/tl/8-Reinforcement/2-Gym/solution/Julia/README.md b/translations/tl/8-Reinforcement/2-Gym/solution/Julia/README.md index 4581e4011..eec993235 100644 --- a/translations/tl/8-Reinforcement/2-Gym/solution/Julia/README.md +++ b/translations/tl/8-Reinforcement/2-Gym/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/8-Reinforcement/2-Gym/solution/R/README.md b/translations/tl/8-Reinforcement/2-Gym/solution/R/README.md index 8f538d6fb..eec993235 100644 --- a/translations/tl/8-Reinforcement/2-Gym/solution/R/README.md +++ b/translations/tl/8-Reinforcement/2-Gym/solution/R/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/tl/8-Reinforcement/README.md b/translations/tl/8-Reinforcement/README.md index c020d71e5..c6c233122 100644 --- a/translations/tl/8-Reinforcement/README.md +++ b/translations/tl/8-Reinforcement/README.md @@ -1,12 +1,3 @@ - # Panimula sa reinforcement learning Ang reinforcement learning, RL, ay itinuturing bilang isa sa mga pangunahing paradigma ng machine learning, kasabay ng supervised learning at unsupervised learning. Ang RL ay tungkol sa paggawa ng mga desisyon: paghahatid ng tamang desisyon o kahit papaano ay pagkatuto mula rito. diff --git a/translations/tl/9-Real-World/1-Applications/README.md b/translations/tl/9-Real-World/1-Applications/README.md index 95d542f57..42d513fbf 100644 --- a/translations/tl/9-Real-World/1-Applications/README.md +++ b/translations/tl/9-Real-World/1-Applications/README.md @@ -1,12 +1,3 @@ - # Postscript: Machine learning sa tunay na mundo ![Buod ng machine learning sa tunay na mundo sa isang sketchnote](../../../../sketchnotes/ml-realworld.png) diff --git a/translations/tl/9-Real-World/1-Applications/assignment.md b/translations/tl/9-Real-World/1-Applications/assignment.md index 3a563c95a..d667ccca8 100644 --- a/translations/tl/9-Real-World/1-Applications/assignment.md +++ b/translations/tl/9-Real-World/1-Applications/assignment.md @@ -1,12 +1,3 @@ - # Isang ML Scavenger Hunt ## Mga Instruksyon diff --git a/translations/tl/9-Real-World/2-Debugging-ML-Models/README.md b/translations/tl/9-Real-World/2-Debugging-ML-Models/README.md index 74d283629..2048f4db9 100644 --- a/translations/tl/9-Real-World/2-Debugging-ML-Models/README.md +++ b/translations/tl/9-Real-World/2-Debugging-ML-Models/README.md @@ -1,12 +1,3 @@ - # Postscript: Pag-debug ng Modelo sa Machine Learning gamit ang mga Komponent ng Responsible AI Dashboard ## [Pre-lecture quiz](https://ff-quizzes.netlify.app/en/ml/) diff --git a/translations/tl/9-Real-World/2-Debugging-ML-Models/assignment.md b/translations/tl/9-Real-World/2-Debugging-ML-Models/assignment.md index 36faf7525..2856335f4 100644 --- a/translations/tl/9-Real-World/2-Debugging-ML-Models/assignment.md +++ b/translations/tl/9-Real-World/2-Debugging-ML-Models/assignment.md @@ -1,12 +1,3 @@ - # Tuklasin ang Responsible AI (RAI) Dashboard ## Mga Tagubilin diff --git a/translations/tl/9-Real-World/README.md b/translations/tl/9-Real-World/README.md index 30208d9b2..96aae5a59 100644 --- a/translations/tl/9-Real-World/README.md +++ b/translations/tl/9-Real-World/README.md @@ -1,12 +1,3 @@ - # Postscript: Mga Totoong Aplikasyon ng Klasikong Machine Learning Sa bahaging ito ng kurikulum, ipakikilala sa iyo ang ilang totoong aplikasyon ng klasikong ML. Nagsaliksik kami sa internet upang makahanap ng mga whitepaper at artikulo tungkol sa mga aplikasyon na gumamit ng mga estratehiyang ito, iniiwasan hangga't maaari ang neural networks, deep learning, at AI. Alamin kung paano ginagamit ang ML sa mga sistema ng negosyo, mga aplikasyon sa ekolohiya, pananalapi, sining at kultura, at marami pang iba. diff --git a/translations/tl/AGENTS.md b/translations/tl/AGENTS.md index 0b88de42d..a8f128d32 100644 --- a/translations/tl/AGENTS.md +++ b/translations/tl/AGENTS.md @@ -1,12 +1,3 @@ - # AGENTS.md ## Pangkalahatang-ideya ng Proyekto diff --git a/translations/tl/CODE_OF_CONDUCT.md b/translations/tl/CODE_OF_CONDUCT.md index 8a88e3c0f..2d7f2c52d 100644 --- a/translations/tl/CODE_OF_CONDUCT.md +++ b/translations/tl/CODE_OF_CONDUCT.md @@ -1,12 +1,3 @@ - # Microsoft Open Source Code of Conduct Ang proyektong ito ay sumunod sa [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/). diff --git a/translations/tl/CONTRIBUTING.md b/translations/tl/CONTRIBUTING.md index 889f780f9..2b0f1e6b3 100644 --- a/translations/tl/CONTRIBUTING.md +++ b/translations/tl/CONTRIBUTING.md @@ -1,12 +1,3 @@ - # Pag-aambag Malugod na tinatanggap ng proyektong ito ang mga ambag at mungkahi. Karamihan sa mga ambag ay nangangailangan ng iyong pagsang-ayon sa isang Contributor License Agreement (CLA) na nagsasaad na may karapatan ka, at tunay mong ibinibigay, ang mga karapatan sa amin upang magamit ang iyong ambag. Para sa mga detalye, bisitahin ang https://cla.microsoft.com. diff --git a/translations/tl/README.md b/translations/tl/README.md index 9c806b450..5fda17562 100644 --- a/translations/tl/README.md +++ b/translations/tl/README.md @@ -1,12 +1,3 @@ - [![GitHub license](https://img.shields.io/github/license/microsoft/ML-For-Beginners.svg)](https://github.com/microsoft/ML-For-Beginners/blob/master/LICENSE) [![GitHub contributors](https://img.shields.io/github/contributors/microsoft/ML-For-Beginners.svg)](https://GitHub.com/microsoft/ML-For-Beginners/graphs/contributors/) [![GitHub issues](https://img.shields.io/github/issues/microsoft/ML-For-Beginners.svg)](https://GitHub.com/microsoft/ML-For-Beginners/issues/) @@ -17,80 +8,80 @@ CO_OP_TRANSLATOR_METADATA: [![GitHub forks](https://img.shields.io/github/forks/microsoft/ML-For-Beginners.svg?style=social&label=Fork)](https://GitHub.com/microsoft/ML-For-Beginners/network/) [![GitHub stars](https://img.shields.io/github/stars/microsoft/ML-For-Beginners.svg?style=social&label=Star)](https://GitHub.com/microsoft/ML-For-Beginners/stargazers/) -### 🌐 Suporta sa Maramihang Wika +### 🌐 Suporta sa Maraming Wika -#### Sinusuportahan sa pamamagitan ng GitHub Action (Automatiko at Palaging Napapanahon) +#### Sinusuportahan sa pamamagitan ng GitHub Action (Awtomatiko at Laging Napapanahon) -[Arabic](../ar/README.md) | [Bengali](../bn/README.md) | [Bulgarian](../bg/README.md) | [Burmese (Myanmar)](../my/README.md) | [Chinese (Simplified)](../zh/README.md) | [Chinese (Traditional, Hong Kong)](../hk/README.md) | [Chinese (Traditional, Macau)](../mo/README.md) | [Chinese (Traditional, Taiwan)](../tw/README.md) | [Croatian](../hr/README.md) | [Czech](../cs/README.md) | [Danish](../da/README.md) | [Dutch](../nl/README.md) | [Estonian](../et/README.md) | [Finnish](../fi/README.md) | [French](../fr/README.md) | [German](../de/README.md) | [Greek](../el/README.md) | [Hebrew](../he/README.md) | [Hindi](../hi/README.md) | [Hungarian](../hu/README.md) | [Indonesian](../id/README.md) | [Italian](../it/README.md) | [Japanese](../ja/README.md) | [Kannada](../kn/README.md) | [Korean](../ko/README.md) | [Lithuanian](../lt/README.md) | [Malay](../ms/README.md) | [Malayalam](../ml/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Nigerian Pidgin](../pcm/README.md) | [Norwegian](../no/README.md) | [Persian (Farsi)](../fa/README.md) | [Polish](../pl/README.md) | [Portuguese (Brazil)](../br/README.md) | [Portuguese (Portugal)](../pt/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Romanian](../ro/README.md) | [Russian](../ru/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Slovak](../sk/README.md) | [Slovenian](../sl/README.md) | [Spanish](../es/README.md) | [Swahili](../sw/README.md) | [Swedish](../sv/README.md) | [Tagalog (Filipino)](./README.md) | [Tamil](../ta/README.md) | [Telugu](../te/README.md) | [Thai](../th/README.md) | [Turkish](../tr/README.md) | [Ukrainian](../uk/README.md) | [Urdu](../ur/README.md) | [Vietnamese](../vi/README.md) +[Arabic](../ar/README.md) | [Bengali](../bn/README.md) | [Bulgarian](../bg/README.md) | [Burmese (Myanmar)](../my/README.md) | [Chinese (Simplified)](../zh-CN/README.md) | [Chinese (Traditional, Hong Kong)](../zh-HK/README.md) | [Chinese (Traditional, Macau)](../zh-MO/README.md) | [Chinese (Traditional, Taiwan)](../zh-TW/README.md) | [Croatian](../hr/README.md) | [Czech](../cs/README.md) | [Danish](../da/README.md) | [Dutch](../nl/README.md) | [Estonian](../et/README.md) | [Finnish](../fi/README.md) | [French](../fr/README.md) | [German](../de/README.md) | [Greek](../el/README.md) | [Hebrew](../he/README.md) | [Hindi](../hi/README.md) | [Hungarian](../hu/README.md) | [Indonesian](../id/README.md) | [Italian](../it/README.md) | [Japanese](../ja/README.md) | [Kannada](../kn/README.md) | [Korean](../ko/README.md) | [Lithuanian](../lt/README.md) | [Malay](../ms/README.md) | [Malayalam](../ml/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Nigerian Pidgin](../pcm/README.md) | [Norwegian](../no/README.md) | [Persian (Farsi)](../fa/README.md) | [Polish](../pl/README.md) | [Portuguese (Brazil)](../pt-BR/README.md) | [Portuguese (Portugal)](../pt-PT/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Romanian](../ro/README.md) | [Russian](../ru/README.md) | [Serbian (Cyrillic)](../sr/README.md) | [Slovak](../sk/README.md) | [Slovenian](../sl/README.md) | [Spanish](../es/README.md) | [Swahili](../sw/README.md) | [Swedish](../sv/README.md) | [Tagalog (Filipino)](./README.md) | [Tamil](../ta/README.md) | [Telugu](../te/README.md) | [Thai](../th/README.md) | [Turkish](../tr/README.md) | [Ukrainian](../uk/README.md) | [Urdu](../ur/README.md) | [Vietnamese](../vi/README.md) -> **Mas gusto mo bang Mag-clone nang Lokal?** +> **Mas gusto mo bang i-Clonate Locally?** -> Kasama sa repository na ito ang 50+ na pagsasalin ng wika na nagpapalaki nang malaki sa laki ng pag-download. Para mag-clone nang walang mga pagsasalin, gamitin ang sparse checkout: +> Kasama sa repositoryong ito ang 50+ na mga salin ng wika na lubhang nagpapalaki ng laki ng i-download. Para mag-clone nang walang mga salin, gamitin ang sparse checkout: > ```bash > git clone --filter=blob:none --sparse https://github.com/microsoft/ML-For-Beginners.git > cd ML-For-Beginners > git sparse-checkout set --no-cone '/*' '!translations' '!translated_images' > ``` -> Binibigyan ka nito ng lahat ng kakailanganin mo para matapos ang kurso nang mas mabilis ang pag-download. +> Bibigyan ka nito ng lahat ng kailangan mo upang makumpleto ang kurso nang mas mabilis ang pag-download. #### Sumali sa Aming Komunidad [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -Mayroon kaming patuloy na Discord learn with AI series, alamin pa at sumali sa amin sa [Learn with AI Series](https://aka.ms/learnwithai/discord) mula Setyembre 18 - 30, 2025. Makakakuha ka ng mga tip at trick sa paggamit ng GitHub Copilot para sa Data Science. +May ongoing kaming Discord learn with AI series, matuto nang higit pa at sumali sa amin sa [Learn with AI Series](https://aka.ms/learnwithai/discord) mula Setyembre 18 - 30, 2025. Makakakuha ka ng mga tip at trick sa paggamit ng GitHub Copilot para sa Data Science. -![Learn with AI series](../../../../translated_images/tl/3.9b58fd8d6c373c20.webp) +![Learn with AI series](../../translated_images/tl/3.9b58fd8d6c373c20.webp) # Machine Learning para sa mga Baguhan - Isang Kurikulum > 🌍 Maglakbay sa buong mundo habang tinutuklasan natin ang Machine Learning gamit ang mga kultura ng mundo 🌍 -Ikinagagalak ng Cloud Advocates sa Microsoft na mag-alok ng 12-linggong kurikulum na may 26 na aralin na lahat tungkol sa **Machine Learning**. Sa kurikulum na ito, matututuhan mo ang tinatawag na **classic machine learning**, na gumagamit pangunahin ang Scikit-learn bilang library at iniiwasan ang deep learning, na tinatalakay sa aming [AI para sa mga Baguhan na kurikulum](https://aka.ms/ai4beginners). Pagsamahin ang mga araling ito sa aming ['Data Science para sa mga Baguhan' na kurikulum](https://aka.ms/ds4beginners), din! +Ikinagagalak ng Cloud Advocates sa Microsoft na ialok ang isang 12-linggong, 26-leksyon na kurikulum tungkol sa **Machine Learning**. Sa kurikulum na ito, matututuhan mo ang tinatawag na **classic machine learning**, gamit pangunahin ang Scikit-learn bilang isang library at iniiwasan ang deep learning, na tinatalakay sa aming [AI for Beginners' curriculum](https://aka.ms/ai4beginners). Isabay ang mga leksyong ito sa aming ['Data Science for Beginners' curriculum](https://aka.ms/ds4beginners), rin! -Maglakbay kasama namin sa buong mundo habang inaaplay namin ang mga klasikong teknik na ito sa datos mula sa maraming bahagi ng mundo. Bawat aralin ay may kasamang pre- at post-lesson quizzes, nakasulat na mga instruksyon para matapos ang aralin, solusyon, takdang-aralin, at iba pa. Ang aming proyekto-based na pedagohiya ay nagpapahintulot sa iyo na matuto habang gumagawa, isang napatunayang paraan para tumagal ang mga bagong kasanayan. +Maglakbay kasama kami sa buong mundo habang inaaplay natin ang mga klasikong teknik na ito sa data mula sa iba't ibang bahagi ng mundo. Bawat leksyon ay may kasamang pre- at post-lesson na pagsusulit, nakasulat na tagubilin para matapos ang leksyon, solusyon, asignatura, at iba pa. Ang aming project-based na metodolohiya ay nagbibigay daan upang matuto ka habang gumagawa, isang subok na paraan para manatili ang mga bagong kasanayan. **✍️ Taos-pusong pasasalamat sa aming mga may-akda** Jen Looper, Stephen Howell, Francesca Lazzeri, Tomomi Imura, Cassie Breviu, Dmitry Soshnikov, Chris Noring, Anirban Mukherjee, Ornella Altunyan, Ruth Yakubu at Amy Boyd -**🎨 Pasasalamat din sa aming mga ilustrador** Tomomi Imura, Dasani Madipalli, at Jen Looper +**🎨 Salamat din sa aming mga illustrator** Tomomi Imura, Dasani Madipalli, at Jen Looper -**🙏 Espesyal na pasasalamat 🙏 sa aming mga Microsoft Student Ambassador na mga awtor, tagasuri, at mga nag-ambag ng nilalaman**, lalo na kina Rishit Dagli, Muhammad Sakib Khan Inan, Rohan Raj, Alexandru Petrescu, Abhishek Jaiswal, Nawrin Tabassum, Ioan Samuila, at Snigdha Agarwal +**🙏 Espesyal na pasasalamat 🙏 sa aming Microsoft Student Ambassador na mga may-akda, tagasuri, at mga kontribyutor sa nilalaman**, partikular kina Rishit Dagli, Muhammad Sakib Khan Inan, Rohan Raj, Alexandru Petrescu, Abhishek Jaiswal, Nawrin Tabassum, Ioan Samuila, at Snigdha Agarwal -**🤩 Dagdag na pasasalamat sa mga Microsoft Student Ambassadors na sina Eric Wanjau, Jasleen Sondhi, at Vidushi Gupta para sa aming mga aralin sa R!** +**🤩 Dagdag na pasasalamat sa Microsoft Student Ambassadors Eric Wanjau, Jasleen Sondhi, at Vidushi Gupta para sa aming mga leksyon sa R!** # Pagsisimula Sundin ang mga hakbang na ito: -1. **I-fork ang Repository**: I-click ang button na "Fork" sa itaas na kanang bahagi ng pahinang ito. -2. **I-clone ang Repository**: `git clone https://github.com/microsoft/ML-For-Beginners.git` +1. **I-fork ang Repositoryo**: Pindutin ang button na "Fork" sa itaas-kanang sulok ng pahinang ito. +2. **I-clone ang Repositoryo**: `git clone https://github.com/microsoft/ML-For-Beginners.git` -> [hanapin ang lahat ng karagdagang mga mapagkukunan para sa kurso na ito sa aming Microsoft Learn na koleksyon](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) +> [hanapin ang lahat ng karagdagang mapagkukunan para sa kursong ito sa aming koleksyon ng Microsoft Learn](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) -> 🔧 **Kailangan ng tulong?** Tingnan ang aming [Troubleshooting Guide](TROUBLESHOOTING.md) para sa mga solusyon sa mga karaniwang isyu sa pag-install, pagsasaayos, at pagpapatakbo ng mga aralin. +> 🔧 **Kailangan ng tulong?** Tingnan ang aming [Troubleshooting Guide](TROUBLESHOOTING.md) para sa mga solusyon sa karaniwang mga isyu sa pag-install, setup, at pagpapatakbo ng mga leksyon. -**[Mga mag-aaral](https://aka.ms/student-page)**, para gamitin ang kurikulum na ito, i-fork ang buong repo sa sarili mong GitHub account at tapusin ang mga ehersisyo nang mag-isa o kasama ang grupo: +**[Mga Estudyante](https://aka.ms/student-page)**, para magamit ang kurikulum na ito, i-fork ang buong repo sa iyong sariling GitHub account at tapusin ang mga ehersisyo nang mag-isa o kasama ang grupo: -- Magsimula sa isang pre-lecture quiz. -- Basahin ang lektura at tapusin ang mga aktibidad, huminto at magnilay-nilay sa bawat knowledge check. -- Subukang likhain ang mga proyekto sa pamamagitan ng pag-unawa sa mga aralin sa halip na patakbuhin ang solusyon na code; gayunpaman, ang code na iyon ay makukuha sa mga `/solution` na folder sa bawat araling nakatuon sa proyekto. -- Kunin ang post-lecture quiz. -- Tapusin ang hamon. -- Tapusin ang takdang-aralin. -- Pagkatapos matapos ang isang grupo ng aralin, bisitahin ang [Discussion Board](https://github.com/microsoft/ML-For-Beginners/discussions) at "matuto nang malakas" sa pamamagitan ng pagpuno sa naaangkop na PAT rubric. Ang 'PAT' ay isang Progress Assessment Tool na isang rubric na pinupunan mo para mapalawak ang iyong pagkatuto. Maaari ka ring mag-react sa iba pang PAT upang sabay-sabay tayong matuto. +- Magsimula sa isang pre-lecture na pagsusulit. +- Basahin ang lektura at kumpletuhin ang mga gawain, huminto at magmuni-muni sa bawat knowledge check. +- Subukang likhain ang mga proyektong ito sa pamamagitan ng pag-unawa sa mga leksyon kaysa sa pagpatakbo ng solution code; gayunpaman, available ang code na iyon sa mga `/solution` folder sa bawat project-oriented na leksyon. +- Kunin ang post-lecture na pagsusulit. +- Kumpletuhin ang hamon. +- Kumpletuhin ang asignatura. +- Pagkatapos makumpleto ang isang grupo ng leksyon, bisitahin ang [Discussion Board](https://github.com/microsoft/ML-For-Beginners/discussions) at "matuto nang malakas" sa pamamagitan ng pagpuno ng angkop na PAT rubric. Ang 'PAT' ay isang Progress Assessment Tool na isang rubric na iyong pinupunan upang palalimin ang iyong pagkatuto. Maaari ka ring mag-react sa ibang PATs upang sabay tayong matuto. -> Para sa karagdagang pag-aaral, inirerekomenda naming sundan ang mga [Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/k7o7tg1gp306q4?WT.mc_id=academic-77952-leestott) na module at landas sa pagkatuto. +> Para sa karagdagang pag-aaral, inirerekomenda naming sundin ang mga ito [Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/k7o7tg1gp306q4?WT.mc_id=academic-77952-leestott) na mga module at learning paths. -**Mga guro**, mayroong kami [ilang suhestiyon](for-teachers.md) kung paano gamitin ang kurikulum na ito. +**Mga Guro**, nagbigay kami ng [ilang mga suhestiyon](for-teachers.md) kung paano gamitin ang kurikulum na ito. --- -## Mga Video na Gabay +## Mga Video walkthrough -Ang ilang mga aralin ay available bilang maikling porma ng video. Makikita mo ang lahat ng ito nang naka-inline sa mga aralin, o sa [ML for Beginners playlist sa Microsoft Developer YouTube channel](https://aka.ms/ml-beginners-videos) sa pamamagitan ng pag-click sa larawan sa ibaba. +Ang ilan sa mga leksyon ay available bilang maikling anyo ng video. Maaari mong matagpuan lahat ng ito nang inline sa mga leksyon, o sa [ML for Beginners playlist sa Microsoft Developer YouTube channel](https://aka.ms/ml-beginners-videos) sa pamamagitan ng pag-click sa larawan sa ibaba. -[![ML for beginners banner](../../../../translated_images/tl/ml-for-beginners-video-banner.63f694a100034bc6.webp)](https://aka.ms/ml-beginners-videos) +[![ML for beginners banner](../../translated_images/tl/ml-for-beginners-video-banner.63f694a100034bc6.webp)](https://aka.ms/ml-beginners-videos) --- @@ -100,79 +91,79 @@ Ang ilang mga aralin ay available bilang maikling porma ng video. Makikita mo an **Gif ni** [Mohit Jaisal](https://linkedin.com/in/mohitjaisal) -> 🎥 I-click ang larawan sa itaas para sa isang video tungkol sa proyekto at mga taong lumikha nito! +> 🎥 I-click ang larawan sa itaas para sa isang video tungkol sa proyekto at sa mga taong lumikha nito! --- -## Pedagogiya +## Pedagohiya -Pinili namin ang dalawang pedagogical na prinsipyo habang ginagawa ang kurikulum na ito: pagtiyak na ito ay hands-on na **project-based** at na ito ay may kasamang mga **madalas na quizzes**. Bukod pa rito, ang kurikulum na ito ay may isang pangkalahatang **tema** upang bigyan ito ng pagkakaugnay-ugnay. +Pinili namin ang dalawang pedagogical tenet habang ginagawa ang kurikulum na ito: pagtitiyak na ito ay hands-on **project-based** at na ito ay may kasamang **madalas na pagsusulit**. Bukod dito, ang kurikulum na ito ay may karaniwang **tema** upang magkaroon ng pagkakaisa. -Sa pamamagitan ng pagtiyak na ang nilalaman ay naaayon sa mga proyekto, ang proseso ay nagiging mas kawili-wili para sa mga mag-aaral at ang pag-alala sa mga konsepto ay mapapalakas. Bukod pa rito, ang isang low-stakes na pagsusulit bago ang klase ay nagtatakda ng intensyon ng mag-aaral sa pag-aaral ng paksa, habang ang pangalawang pagsusulit pagkatapos ng klase ay nagsisiguro ng karagdagang pag-alala. Ang kurikulum na ito ay dinisenyo upang maging flexible at masaya at maaaring kunin nang buo o kalahati lamang. Nagsisimula ang mga proyekto sa maliit at nagiging mas komplikado sa katapusan ng 12-linggong siklo. Kabilang din sa kurikulum na ito ang isang postscript tungkol sa mga tunay na aplikasyon ng ML, na maaaring gamitin bilang dagdag na kredito o bilang batayan para sa diskusyon. +Sa pagtitiyak na ang nilalaman ay naka-align sa mga proyekto, nagiging mas nakaka-engganyo ang proseso para sa mga estudyante at nadaragdagan ang retention ng mga konsepto. Dagdag pa, ang isang low-stakes na pagsusulit bago ang klase ay nagtatakda ng layunin ng estudyante na matuto ng isang paksa, habang ang pangalawang pagsusulit pagkatapos ng klase ay nagsisiguro ng karagdagang retention. Ang kurikulum na ito ay dinisenyo upang maging flexible at masaya at maaaring kunin nang buo o bahagi. Ang mga proyekto ay nagsisimula sa maliit at unti-unting nagiging kumplikado sa pagtatapos ng 12-linggong siklo. Kasama rin sa kurikulum na ito ang isang postscript tungkol sa mga totoong aplikasyon ng ML, na maaaring gamitin bilang dagdag na kredito o bilang basehan ng diskusyon. -> Hanapin ang aming [Code of Conduct](CODE_OF_CONDUCT.md), [Contributing](CONTRIBUTING.md), [Translation](TRANSLATIONS.md), at [Troubleshooting](TROUBLESHOOTING.md) na mga gabay. Malugod naming tinatanggap ang inyong kapaki-pakinabang na puna! +> Hanapin ang aming [Code of Conduct](CODE_OF_CONDUCT.md), [Contributing](CONTRIBUTING.md), [Translation](TRANSLATIONS.md), at [Troubleshooting](TROUBLESHOOTING.md) na mga patnubay. Malugod naming tinatanggap ang iyong makabuluhang puna! -## Kasama sa bawat aralin +## Bawat leksyon ay may kasamang - opsyonal na sketchnote -- opsyonal na dagdag na video -- video walkthrough (ilang aralin lamang) +- opsyonal na karagdagang video +- video walkthrough (ilang mga leksyon lamang) - [pre-lecture warmup quiz](https://ff-quizzes.netlify.app/en/ml/) -- nakasulat na aralin -- para sa mga aralin na nakatuon sa proyekto, mga hakbang-hakbang na gabay kung paano buuin ang proyekto +- nakasulat na leksyon +- para sa mga project-based na leksyon, step-by-step na mga gabay kung paano buuin ang proyekto - knowledge checks - isang hamon -- dagdag na babasahin -- takdang-aralin +- karagdagang babasahin +- asignatura - [post-lecture quiz](https://ff-quizzes.netlify.app/en/ml/) -> **Isang paalala tungkol sa mga wika**: Pangunahing nakasulat sa Python ang mga araling ito, ngunit marami rin ang available sa R. Para matapos ang isang aralin sa R, pumunta sa folder na `/solution` at hanapin ang mga aralin sa R. Kasama rito ang extension na .rmd na nangangahulugang isang **R Markdown** na file na simpleng tinukoy bilang isang pagsasama ng `code chunks` (ng R o iba pang mga wika) at isang `YAML header` (na gumagabay kung paano iformat ang mga output tulad ng PDF) sa isang `Markdown document`. Dahil dito, nagsisilbi itong isang halimbawa ng authoring framework para sa data science dahil pinapahintulutan kang pagsamahin ang iyong code, ang output nito, at ang iyong mga saloobin sa pamamagitan ng pagsusulat ng mga ito sa Markdown. Bukod dito, maaaring i-render ang mga dokumento ng R Markdown sa mga output format tulad ng PDF, HTML, o Word. -> **Isang tala tungkol sa mga pagsusulit**: Lahat ng pagsusulit ay nakapaloob sa [Quiz App folder](../../quiz-app), para sa kabuuang 52 pagsusulit na may tig-tlong tanong bawat isa. Ito ay naka-link mula sa loob ng mga aralin ngunit ang quiz app ay pwedeng patakbuhin nang lokal; sundin ang mga tagubilin sa `quiz-app` folder upang mag-host nang lokal o mag-deploy sa Azure. - -| Lesson Number | Topic | Lesson Grouping | Learning Objectives | Linked Lesson | Author | -| :-----------: | :------------------------------------------------------------: | :-------------------------------------------------: | ------------------------------------------------------------------------------------------------------------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------: | -| 01 | Panimula sa machine learning | [Introduction](1-Introduction/README.md) | Matutunan ang mga pangunahing konsepto sa likod ng machine learning | [Lesson](1-Introduction/1-intro-to-ML/README.md) | Muhammad | -| 02 | Kasaysayan ng machine learning | [Introduction](1-Introduction/README.md) | Matutunan ang kasaysayan sa likod ng larangang ito | [Lesson](1-Introduction/2-history-of-ML/README.md) | Jen and Amy | -| 03 | Katarungan at machine learning | [Introduction](1-Introduction/README.md) | Ano ang mahahalagang isyung pilosopikal tungkol sa katarungan na dapat isaalang-alang ng mga estudyante sa pagbuo at aplikasyon ng ML models? | [Lesson](1-Introduction/3-fairness/README.md) | Tomomi | -| 04 | Teknik para sa machine learning | [Introduction](1-Introduction/README.md) | Anong mga teknik ang ginagamit ng mga mananaliksik sa ML para gumawa ng ML models? | [Lesson](1-Introduction/4-techniques-of-ML/README.md) | Chris and Jen | -| 05 | Panimula sa regression | [Regression](2-Regression/README.md) | Magsimula sa Python at Scikit-learn para sa mga regression model | [Python](2-Regression/1-Tools/README.md) • [R](../../2-Regression/1-Tools/solution/R/lesson_1.html) | Jen • Eric Wanjau | -| 06 | Presyo ng kalabasa sa Hilagang Amerika 🎃 | [Regression](2-Regression/README.md) | I-visualize at linisin ang datos bilang paghahanda sa ML | [Python](2-Regression/2-Data/README.md) • [R](../../2-Regression/2-Data/solution/R/lesson_2.html) | Jen • Eric Wanjau | -| 07 | Presyo ng kalabasa sa Hilagang Amerika 🎃 | [Regression](2-Regression/README.md) | Gumawa ng linear at polynomial regression models | [Python](2-Regression/3-Linear/README.md) • [R](../../2-Regression/3-Linear/solution/R/lesson_3.html) | Jen and Dmitry • Eric Wanjau | -| 08 | Presyo ng kalabasa sa Hilagang Amerika 🎃 | [Regression](2-Regression/README.md) | Gumawa ng logistic regression model | [Python](2-Regression/4-Logistic/README.md) • [R](../../2-Regression/4-Logistic/solution/R/lesson_4.html) | Jen • Eric Wanjau | -| 09 | Isang Web App 🔌 | [Web App](3-Web-App/README.md) | Gumawa ng web app para gamitin ang iyong na-train na modelo | [Python](3-Web-App/1-Web-App/README.md) | Jen | -| 10 | Panimula sa classification | [Classification](4-Classification/README.md) | Linisin, ihanda, at i-visualize ang iyong datos; panimula sa classification | [Python](4-Classification/1-Introduction/README.md) • [R](../../4-Classification/1-Introduction/solution/R/lesson_10.html) | Jen and Cassie • Eric Wanjau | -| 11 | Masasarap na pagkaing Asyano at Indian 🍜 | [Classification](4-Classification/README.md) | Panimula sa mga classifiers | [Python](4-Classification/2-Classifiers-1/README.md) • [R](../../4-Classification/2-Classifiers-1/solution/R/lesson_11.html) | Jen and Cassie • Eric Wanjau | -| 12 | Masasarap na pagkaing Asyano at Indian 🍜 | [Classification](4-Classification/README.md) | Higit pang mga classifiers | [Python](4-Classification/3-Classifiers-2/README.md) • [R](../../4-Classification/3-Classifiers-2/solution/R/lesson_12.html) | Jen and Cassie • Eric Wanjau | -| 13 | Masasarap na pagkaing Asyano at Indian 🍜 | [Classification](4-Classification/README.md) | Gumawa ng recommender web app gamit ang iyong modelo | [Python](4-Classification/4-Applied/README.md) | Jen | -| 14 | Panimula sa clustering | [Clustering](5-Clustering/README.md) | Linisin, ihanda, at i-visualize ang iyong datos; panimula sa clustering | [Python](5-Clustering/1-Visualize/README.md) • [R](../../5-Clustering/1-Visualize/solution/R/lesson_14.html) | Jen • Eric Wanjau | -| 15 | Pagsusuri ng mga musikang Nigerian 🎧 | [Clustering](5-Clustering/README.md) | Suriin ang K-Means clustering method | [Python](5-Clustering/2-K-Means/README.md) • [R](../../5-Clustering/2-K-Means/solution/R/lesson_15.html) | Jen • Eric Wanjau | -| 16 | Panimula sa natural language processing ☕️ | [Natural language processing](6-NLP/README.md) | Matutunan ang mga batayan ng NLP sa paggawa ng isang simpleng bot | [Python](6-NLP/1-Introduction-to-NLP/README.md) | Stephen | -| 17 | Karaniwang mga Gawain sa NLP ☕️ | [Natural language processing](6-NLP/README.md) | Palalimin ang iyong kaalaman sa NLP sa pamamagitan ng pag-unawa sa mga karaniwang gawain sa pagtatrabaho sa mga istruktura ng wika | [Python](6-NLP/2-Tasks/README.md) | Stephen | -| 18 | Pagsasalin at pagsusuri ng damdamin ♥️ | [Natural language processing](6-NLP/README.md) | Pagsasalin at pagsusuri ng damdamin gamit si Jane Austen | [Python](6-NLP/3-Translation-Sentiment/README.md) | Stephen | -| 19 | Mga romantikong hotel ng Europa ♥️ | [Natural language processing](6-NLP/README.md) | Pagsusuri ng damdamin gamit ang mga review ng hotel 1 | [Python](6-NLP/4-Hotel-Reviews-1/README.md) | Stephen | -| 20 | Mga romantikong hotel ng Europa ♥️ | [Natural language processing](6-NLP/README.md) | Pagsusuri ng damdamin gamit ang mga review ng hotel 2 | [Python](6-NLP/5-Hotel-Reviews-2/README.md) | Stephen | -| 21 | Panimula sa time series forecasting | [Time series](7-TimeSeries/README.md) | Panimula sa time series forecasting | [Python](7-TimeSeries/1-Introduction/README.md) | Francesca | -| 22 | ⚡️ Paggamit ng Kuryente sa Mundo ⚡️ - time series forecasting gamit ARIMA | [Time series](7-TimeSeries/README.md) | Time series forecasting gamit ang ARIMA | [Python](7-TimeSeries/2-ARIMA/README.md) | Francesca | -| 23 | ⚡️ Paggamit ng Kuryente sa Mundo ⚡️ - time series forecasting gamit SVR | [Time series](7-TimeSeries/README.md) | Time series forecasting gamit ang Support Vector Regressor | [Python](7-TimeSeries/3-SVR/README.md) | Anirban | -| 24 | Panimula sa reinforcement learning | [Reinforcement learning](8-Reinforcement/README.md) | Panimula sa reinforcement learning gamit ang Q-Learning | [Python](8-Reinforcement/1-QLearning/README.md) | Dmitry | -| 25 | Tulungan si Peter na iwasan ang lobo! 🐺 | [Reinforcement learning](8-Reinforcement/README.md) | Reinforcement learning Gym | [Python](8-Reinforcement/2-Gym/README.md) | Dmitry | -| Postscript | Mga totoong senaryo at aplikasyon ng ML | [ML in the Wild](9-Real-World/README.md) | Mga kawili-wili at nagbibigay-liwanag na totoong aplikasyon ng klasikal na ML | [Lesson](9-Real-World/1-Applications/README.md) | Team | -| Postscript | Pag-debug ng Modelo sa ML gamit ang RAI dashboard | [ML in the Wild](9-Real-World/README.md) | Pag-debug ng Modelo sa Machine Learning gamit ang Responsible AI dashboard components | [Lesson](9-Real-World/2-Debugging-ML-Models/README.md) | Ruth Yakubu | - -> [hanapin lahat ng karagdagang mga resources para sa kursong ito sa aming Microsoft Learn collection](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) +> **Tungkol sa mga wika**: Pangunahing nakasulat sa Python ang mga leksyong ito, ngunit marami rin ang available sa R. Para matapos ang isang R na leksyon, pumunta sa folder na `/solution` at hanapin ang mga R na leksyon. Mayroon silang .rmd extension na kumakatawan sa isang **R Markdown** file na maaaring ilarawan bilang isang pag-embed ng `code chunks` (ng R o ibang mga wika) at isang `YAML header` (na naggagabay kung paano i-format ang output gaya ng PDF) sa isang `Markdown document`. Kaya, nagsisilbi itong isang halimbawang authoring framework para sa data science dahil pinapayagan kang pagsamahin ang iyong code, ang output nito, at ang iyong mga ideya sa pagsulat ng mga ito sa Markdown. Bukod dito, ang mga R Markdown document ay maaaring i-render sa mga output format gaya ng PDF, HTML, o Word. +> **Isang paalala tungkol sa mga pagsusulit**: Lahat ng pagsusulit ay nakapaloob sa [Quiz App folder](../../quiz-app), para sa kabuuang 52 na pagsusulit na may tig-tatlong tanong bawat isa. Nakalink ito mula sa loob ng mga aralin ngunit maaaring patakbuhin nang lokal ang quiz app; sundin ang mga tagubilin sa `quiz-app` folder upang i-host nang lokal o i-deploy sa Azure. + +| Lesson Number | Paksa | Pangkat ng Aralin | Mga Layunin sa Pagkatuto | Nakalink na Aralin | May-akda | +| :-----------: | :-----------------------------------------------------------: | :---------------------------------------------------: | ------------------------------------------------------------------------------------------------------------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------: | :----------------------------------------------------: | +| 01 | Panimula sa machine learning | [Introduction](1-Introduction/README.md) | Matutuhan ang mga pangunahing konsepto sa likod ng machine learning | [Lesson](1-Introduction/1-intro-to-ML/README.md) | Muhammad | +| 02 | Kasaysayan ng machine learning | [Introduction](1-Introduction/README.md) | Matutuhan ang kasaysayan na nasa likod ng larangang ito | [Lesson](1-Introduction/2-history-of-ML/README.md) | Jen at Amy | +| 03 | Katarungan at machine learning | [Introduction](1-Introduction/README.md) | Ano ang mahahalagang pilosopikal na isyu tungkol sa katarungan na dapat isaalang-alang ng mga estudyante sa pagbuo at paggamit ng mga modelo ng ML? | [Lesson](1-Introduction/3-fairness/README.md) | Tomomi | +| 04 | Mga teknik para sa machine learning | [Introduction](1-Introduction/README.md) | Anong mga teknik ang ginagamit ng mga mananaliksik ng ML upang bumuo ng mga modelo? | [Lesson](1-Introduction/4-techniques-of-ML/README.md) | Chris at Jen | +| 05 | Panimula sa regression | [Regression](2-Regression/README.md) | Magsimula sa Python at Scikit-learn para sa mga modelo ng regression | [Python](2-Regression/1-Tools/README.md) • [R](../../2-Regression/1-Tools/solution/R/lesson_1.html) | Jen • Eric Wanjau | +| 06 | Mga presyo ng kalabasa sa North America 🎃 | [Regression](2-Regression/README.md) | I-visualize at linisin ang data bilang paghahanda para sa ML | [Python](2-Regression/2-Data/README.md) • [R](../../2-Regression/2-Data/solution/R/lesson_2.html) | Jen • Eric Wanjau | +| 07 | Mga presyo ng kalabasa sa North America 🎃 | [Regression](2-Regression/README.md) | Bumuo ng linear at polynomial na mga modelo ng regression | [Python](2-Regression/3-Linear/README.md) • [R](../../2-Regression/3-Linear/solution/R/lesson_3.html) | Jen at Dmitry • Eric Wanjau | +| 08 | Mga presyo ng kalabasa sa North America 🎃 | [Regression](2-Regression/README.md) | Bumuo ng modelo ng logistic regression | [Python](2-Regression/4-Logistic/README.md) • [R](../../2-Regression/4-Logistic/solution/R/lesson_4.html) | Jen • Eric Wanjau | +| 09 | Isang Web App 🔌 | [Web App](3-Web-App/README.md) | Gumawa ng web app upang magamit ang iyong na-train na modelo | [Python](3-Web-App/1-Web-App/README.md) | Jen | +| 10 | Panimula sa classification | [Classification](4-Classification/README.md) | Linisin, ihanda, at i-visualize ang iyong data; panimula sa classification | [Python](4-Classification/1-Introduction/README.md) • [R](../../4-Classification/1-Introduction/solution/R/lesson_10.html) | Jen at Cassie • Eric Wanjau | +| 11 | Masasarap na lutuin ng Asya at India 🍜 | [Classification](4-Classification/README.md) | Panimula sa mga classifier | [Python](4-Classification/2-Classifiers-1/README.md) • [R](../../4-Classification/2-Classifiers-1/solution/R/lesson_11.html) | Jen at Cassie • Eric Wanjau | +| 12 | Masasarap na lutuin ng Asya at India 🍜 | [Classification](4-Classification/README.md) | Higit pang mga classifier | [Python](4-Classification/3-Classifiers-2/README.md) • [R](../../4-Classification/3-Classifiers-2/solution/R/lesson_12.html) | Jen at Cassie • Eric Wanjau | +| 13 | Masasarap na lutuin ng Asya at India 🍜 | [Classification](4-Classification/README.md) | Bumuo ng web app na nagpapayo gamit ang iyong modelo | [Python](4-Classification/4-Applied/README.md) | Jen | +| 14 | Panimula sa clustering | [Clustering](5-Clustering/README.md) | Linisin, ihanda, at i-visualize ang iyong data; Panimula sa clustering | [Python](5-Clustering/1-Visualize/README.md) • [R](../../5-Clustering/1-Visualize/solution/R/lesson_14.html) | Jen • Eric Wanjau | +| 15 | Paggalugad ng mga paboritong tugtugin sa Nigeria 🎧 | [Clustering](5-Clustering/README.md) | Galugarin ang K-Means clustering method | [Python](5-Clustering/2-K-Means/README.md) • [R](../../5-Clustering/2-K-Means/solution/R/lesson_15.html) | Jen • Eric Wanjau | +| 16 | Panimula sa natural language processing ☕️ | [Natural language processing](6-NLP/README.md) | Matutuhan ang mga pangunahing kaalaman tungkol sa NLP sa pamamagitan ng paggawa ng simpleng bot | [Python](6-NLP/1-Introduction-to-NLP/README.md) | Stephen | +| 17 | Mga Karaniwang Gawain sa NLP ☕️ | [Natural language processing](6-NLP/README.md) | Palalimin ang iyong kaalaman sa NLP sa pamamagitan ng pag-unawa sa mga karaniwang gawain na kinakailangan sa pagharap sa mga istruktura ng wika | [Python](6-NLP/2-Tasks/README.md) | Stephen | +| 18 | Pagsasalin at pagsusuri ng damdamin ♥️ | [Natural language processing](6-NLP/README.md) | Pagsasalin at pagsusuri ng damdamin gamit si Jane Austen | [Python](6-NLP/3-Translation-Sentiment/README.md) | Stephen | +| 19 | Mga romantikong hotel sa Europa ♥️ | [Natural language processing](6-NLP/README.md) | Pagsusuri ng damdamin gamit ang mga review ng hotel 1 | [Python](6-NLP/4-Hotel-Reviews-1/README.md) | Stephen | +| 20 | Mga romantikong hotel sa Europa ♥️ | [Natural language processing](6-NLP/README.md) | Pagsusuri ng damdamin gamit ang mga review ng hotel 2 | [Python](6-NLP/5-Hotel-Reviews-2/README.md) | Stephen | +| 21 | Panimula sa pagsusuri ng time series | [Time series](7-TimeSeries/README.md) | Panimula sa pagsusuri ng time series | [Python](7-TimeSeries/1-Introduction/README.md) | Francesca | +| 22 | ⚡️ Paggamit ng Lakas sa Mundo ⚡️ - pagsusuri ng time series gamit ang ARIMA | [Time series](7-TimeSeries/README.md) | Pagsusuri ng time series gamit ang ARIMA | [Python](7-TimeSeries/2-ARIMA/README.md) | Francesca | +| 23 | ⚡️ Paggamit ng Lakas sa Mundo ⚡️ - pagsusuri ng time series gamit ang SVR | [Time series](7-TimeSeries/README.md) | Pagsusuri ng time series gamit ang Support Vector Regressor | [Python](7-TimeSeries/3-SVR/README.md) | Anirban | +| 24 | Panimula sa reinforcement learning | [Reinforcement learning](8-Reinforcement/README.md) | Panimula sa reinforcement learning gamit ang Q-Learning | [Python](8-Reinforcement/1-QLearning/README.md) | Dmitry | +| 25 | Tulungan si Peter na iwasan ang lobo! 🐺 | [Reinforcement learning](8-Reinforcement/README.md) | Reinforcement learning Gym | [Python](8-Reinforcement/2-Gym/README.md) | Dmitry | +| Postscript | Mga totoong sitwasyon at aplikasyon ng ML | [ML in the Wild](9-Real-World/README.md) | Mga kawili-wili at nakakahulugang aplikasyon ng klasikong ML sa totoong mundo | [Lesson](9-Real-World/1-Applications/README.md) | Team | +| Postscript | Pag-debug ng Modelo sa ML gamit ang RAI dashboard | [ML in the Wild](9-Real-World/README.md) | Pag-debug ng modelo sa Machine Learning gamit ang Responsible AI dashboard components | [Lesson](9-Real-World/2-Debugging-ML-Models/README.md) | Ruth Yakubu | + +> [hanapin ang lahat ng karagdagang mga mapagkukunan para sa kursong ito sa aming Microsoft Learn collection](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) ## Offline access -Maaari mong patakbuhin ang dokumentasyong ito offline gamit ang [Docsify](https://docsify.js.org/#/). I-fork ang repo na ito, [i-install ang Docsify](https://docsify.js.org/#/quickstart) sa iyong lokal na makina, at pagkatapos sa root folder ng repo na ito, i-type ang `docsify serve`. Ang website ay ise-serve sa port 3000 sa iyong localhost: `localhost:3000`. +Maaari mong patakbuhin ang dokumentasyong ito offline gamit ang [Docsify](https://docsify.js.org/#/). I-fork ang repo na ito, [i-install ang Docsify](https://docsify.js.org/#/quickstart) sa iyong lokal na makina, at pagkatapos ay sa root folder ng repo na ito, i-type ang `docsify serve`. Ang website ay ihahain sa port 3000 sa iyong localhost: `localhost:3000`. ## PDFs Hanapin ang pdf ng kurikulum na may mga link [dito](https://microsoft.github.io/ML-For-Beginners/pdf/readme.pdf). -## 🎒 Iba pang Mga Kurso +## 🎒 Iba Pang Mga Kurso -Ang aming koponan ay gumagawa ng iba pang mga kurso! Tignan: +Ang aming koponan ay gumagawa ng iba pang mga kurso! Tingnan ang: ### LangChain @@ -190,7 +181,7 @@ Ang aming koponan ay gumagawa ng iba pang mga kurso! Tignan: --- ### Generative AI Series -[![Generative AI para sa mga Nagsisimula](https://img.shields.io/badge/Generative%20AI%20for%20Beginners-8B5CF6?style=for-the-badge&labelColor=E5E7EB&color=8B5CF6)](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-105485-koreyst) +[![Generative AI para sa mga Baguhan](https://img.shields.io/badge/Generative%20AI%20for%20Beginners-8B5CF6?style=for-the-badge&labelColor=E5E7EB&color=8B5CF6)](https://github.com/microsoft/generative-ai-for-beginners?WT.mc_id=academic-105485-koreyst) [![Generative AI (.NET)](https://img.shields.io/badge/Generative%20AI%20(.NET)-9333EA?style=for-the-badge&labelColor=E5E7EB&color=9333EA)](https://github.com/microsoft/Generative-AI-for-beginners-dotnet?WT.mc_id=academic-105485-koreyst) [![Generative AI (Java)](https://img.shields.io/badge/Generative%20AI%20(Java)-C084FC?style=for-the-badge&labelColor=E5E7EB&color=C084FC)](https://github.com/microsoft/generative-ai-for-beginners-java?WT.mc_id=academic-105485-koreyst) [![Generative AI (JavaScript)](https://img.shields.io/badge/Generative%20AI%20(JavaScript)-E879F9?style=for-the-badge&labelColor=E5E7EB&color=E879F9)](https://github.com/microsoft/generative-ai-with-javascript?WT.mc_id=academic-105485-koreyst) @@ -198,13 +189,13 @@ Ang aming koponan ay gumagawa ng iba pang mga kurso! Tignan: --- ### Pangunahing Pagkatuto -[![ML para sa mga Nagsisimula](https://img.shields.io/badge/ML%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=22C55E)](https://aka.ms/ml-beginners?WT.mc_id=academic-105485-koreyst) -[![Data Science para sa mga Nagsisimula](https://img.shields.io/badge/Data%20Science%20for%20Beginners-84CC16?style=for-the-badge&labelColor=E5E7EB&color=84CC16)](https://aka.ms/datascience-beginners?WT.mc_id=academic-105485-koreyst) -[![AI para sa mga Nagsisimula](https://img.shields.io/badge/AI%20for%20Beginners-A3E635?style=for-the-badge&labelColor=E5E7EB&color=A3E635)](https://aka.ms/ai-beginners?WT.mc_id=academic-105485-koreyst) -[![Cybersecurity para sa mga Nagsisimula](https://img.shields.io/badge/Cybersecurity%20for%20Beginners-F97316?style=for-the-badge&labelColor=E5E7EB&color=F97316)](https://github.com/microsoft/Security-101?WT.mc_id=academic-96948-sayoung) -[![Web Dev para sa mga Nagsisimula](https://img.shields.io/badge/Web%20Dev%20for%20Beginners-EC4899?style=for-the-badge&labelColor=E5E7EB&color=EC4899)](https://aka.ms/webdev-beginners?WT.mc_id=academic-105485-koreyst) -[![IoT para sa mga Nagsisimula](https://img.shields.io/badge/IoT%20for%20Beginners-14B8A6?style=for-the-badge&labelColor=E5E7EB&color=14B8A6)](https://aka.ms/iot-beginners?WT.mc_id=academic-105485-koreyst) -[![XR Development para sa mga Nagsisimula](https://img.shields.io/badge/XR%20Development%20for%20Beginners-38BDF8?style=for-the-badge&labelColor=E5E7EB&color=38BDF8)](https://github.com/microsoft/xr-development-for-beginners?WT.mc_id=academic-105485-koreyst) +[![ML para sa mga Baguhan](https://img.shields.io/badge/ML%20for%20Beginners-22C55E?style=for-the-badge&labelColor=E5E7EB&color=22C55E)](https://aka.ms/ml-beginners?WT.mc_id=academic-105485-koreyst) +[![Agham ng Datos para sa mga Baguhan](https://img.shields.io/badge/Data%20Science%20for%20Beginners-84CC16?style=for-the-badge&labelColor=E5E7EB&color=84CC16)](https://aka.ms/datascience-beginners?WT.mc_id=academic-105485-koreyst) +[![AI para sa mga Baguhan](https://img.shields.io/badge/AI%20for%20Beginners-A3E635?style=for-the-badge&labelColor=E5E7EB&color=A3E635)](https://aka.ms/ai-beginners?WT.mc_id=academic-105485-koreyst) +[![Cybersecurity para sa mga Baguhan](https://img.shields.io/badge/Cybersecurity%20for%20Beginners-F97316?style=for-the-badge&labelColor=E5E7EB&color=F97316)](https://github.com/microsoft/Security-101?WT.mc_id=academic-96948-sayoung) +[![Web Dev para sa mga Baguhan](https://img.shields.io/badge/Web%20Dev%20for%20Beginners-EC4899?style=for-the-badge&labelColor=E5E7EB&color=EC4899)](https://aka.ms/webdev-beginners?WT.mc_id=academic-105485-koreyst) +[![IoT para sa mga Baguhan](https://img.shields.io/badge/IoT%20for%20Beginners-14B8A6?style=for-the-badge&labelColor=E5E7EB&color=14B8A6)](https://aka.ms/iot-beginners?WT.mc_id=academic-105485-koreyst) +[![XR Development para sa mga Baguhan](https://img.shields.io/badge/XR%20Development%20for%20Beginners-38BDF8?style=for-the-badge&labelColor=E5E7EB&color=38BDF8)](https://github.com/microsoft/xr-development-for-beginners?WT.mc_id=academic-105485-koreyst) --- @@ -216,17 +207,17 @@ Ang aming koponan ay gumagawa ng iba pang mga kurso! Tignan: ## Pagkuha ng Tulong -Kung ikaw ay naiipit o may mga katanungan tungkol sa paggawa ng mga AI app, sumali sa mga kapwa nag-aaral at mga bihasang developer sa mga talakayan tungkol sa MCP. Isa itong suportadong komunidad kung saan malugod tinatanggap ang mga tanong at malayang naibabahagi ang kaalaman. +Kung ikaw ay naipit o may mga tanong tungkol sa paggawa ng mga AI app. Sumali sa mga kapwa nag-aaral at mga bihasang developer sa mga talakayan tungkol sa MCP. Isa itong suportadong komunidad kung saan malugod ang mga tanong at malaya ang pagbabahagi ng kaalaman. [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -Kung mayroon kang puna sa produkto o mga error habang nagbuo, bisitahin: +Kung mayroon kang feedback sa produkto o mga error habang gumagawa, bisitahin ang: [![Microsoft Foundry Developer Forum](https://img.shields.io/badge/GitHub-Microsoft_Foundry_Developer_Forum-blue?style=for-the-badge&logo=github&color=000000&logoColor=fff)](https://aka.ms/foundry/forum) --- -**Paalala**: -Ang dokumentong ito ay isinalin gamit ang AI translation service na [Co-op Translator](https://github.com/Azure/co-op-translator). Habang aming pinagsisikapang maging tumpak ang pagsasalin, pakatandaan na ang awtomatikong pagsasalin ay maaaring maglaman ng mga pagkakamali o di-katiyakan. Ang orihinal na dokumento sa sariling wika nito ang dapat ituring na pangunahing sanggunian. Para sa mahahalagang impormasyon, inirerekomenda ang propesyonal na pagsasalin ng tao. Hindi kami mananagot sa anumang hindi pagkakaunawaan o maling interpretasyon na nagmumula sa paggamit ng pagsasaling ito. +**Paunawa**: +Ang dokumentong ito ay isinalin gamit ang serbisyong AI na pagsasalin na [Co-op Translator](https://github.com/Azure/co-op-translator). Bagama't aming pinagsisikapan ang katumpakan, pakatandaan na ang mga awtomatikong pagsasalin ay maaaring maglaman ng mga pagkakamali o hindi pagkakatugma. Ang orihinal na dokumento sa kanyang orihinal na wika ang dapat ituring na pangunahing sanggunian. Para sa mga mahahalagang impormasyon, inirerekomenda ang propesyonal na pagsasalin ng tao. Hindi kami mananagot sa anumang hindi pagkakaunawaan o maling interpretasyon na maaaring magmula sa paggamit ng pagsasaling ito. \ No newline at end of file diff --git a/translations/tl/SECURITY.md b/translations/tl/SECURITY.md index 5b673c3c4..f97e039bf 100644 --- a/translations/tl/SECURITY.md +++ b/translations/tl/SECURITY.md @@ -1,12 +1,3 @@ - ## Seguridad Seryoso ang Microsoft sa seguridad ng aming mga produkto at serbisyo, kabilang na ang lahat ng source code repositories na pinamamahalaan sa pamamagitan ng aming mga organisasyon sa GitHub, tulad ng [Microsoft](https://github.com/Microsoft), [Azure](https://github.com/Azure), [DotNet](https://github.com/dotnet), [AspNet](https://github.com/aspnet), [Xamarin](https://github.com/xamarin), at [aming mga organisasyon sa GitHub](https://opensource.microsoft.com/). diff --git a/translations/tl/SUPPORT.md b/translations/tl/SUPPORT.md index c39181c29..aca81448e 100644 --- a/translations/tl/SUPPORT.md +++ b/translations/tl/SUPPORT.md @@ -1,12 +1,3 @@ - # Suporta ## Paano maghain ng mga isyu at humingi ng tulong diff --git a/translations/tl/TROUBLESHOOTING.md b/translations/tl/TROUBLESHOOTING.md index 9806f66cd..cf7027148 100644 --- a/translations/tl/TROUBLESHOOTING.md +++ b/translations/tl/TROUBLESHOOTING.md @@ -1,12 +1,3 @@ - # Gabay sa Pag-aayos ng Problema Ang gabay na ito ay makakatulong sa iyo na lutasin ang mga karaniwang problema kapag ginagamit ang kurikulum ng Machine Learning for Beginners. Kung hindi mo makita ang solusyon dito, maaari mong bisitahin ang aming [Discord Discussions](https://aka.ms/foundry/discord) o [magbukas ng isyu](https://github.com/microsoft/ML-For-Beginners/issues). diff --git a/translations/tl/docs/_sidebar.md b/translations/tl/docs/_sidebar.md index 830f3bfa6..13ff1d15d 100644 --- a/translations/tl/docs/_sidebar.md +++ b/translations/tl/docs/_sidebar.md @@ -1,12 +1,3 @@ - - Panimula - [Panimula sa Machine Learning](../1-Introduction/1-intro-to-ML/README.md) - [Kasaysayan ng Machine Learning](../1-Introduction/2-history-of-ML/README.md) diff --git a/translations/tl/for-teachers.md b/translations/tl/for-teachers.md index ef9148f1d..b663240b7 100644 --- a/translations/tl/for-teachers.md +++ b/translations/tl/for-teachers.md @@ -1,12 +1,3 @@ - ## Para sa mga Guro Gusto mo bang gamitin ang kurikulum na ito sa iyong klase? Huwag mag-atubiling gawin ito! diff --git a/translations/tl/quiz-app/README.md b/translations/tl/quiz-app/README.md index 2b27e253e..bdd25e783 100644 --- a/translations/tl/quiz-app/README.md +++ b/translations/tl/quiz-app/README.md @@ -1,12 +1,3 @@ - # Mga Pagsusulit Ang mga pagsusulit na ito ay pre- at post-lecture quizzes para sa ML curriculum sa https://aka.ms/ml-beginners diff --git a/translations/tl/sketchnotes/LICENSE.md b/translations/tl/sketchnotes/LICENSE.md index 5b1c2ddf7..b558d579e 100644 --- a/translations/tl/sketchnotes/LICENSE.md +++ b/translations/tl/sketchnotes/LICENSE.md @@ -1,12 +1,3 @@ - Attribution-ShareAlike 4.0 International ======================================================================= diff --git a/translations/tl/sketchnotes/README.md b/translations/tl/sketchnotes/README.md index fb10c2423..230d37773 100644 --- a/translations/tl/sketchnotes/README.md +++ b/translations/tl/sketchnotes/README.md @@ -1,12 +1,3 @@ - Ang lahat ng sketchnotes ng kurikulum ay maaaring ma-download dito. 🖨 Para sa pag-print sa mataas na resolusyon, ang mga bersyong TIFF ay makikita sa [repo na ito](https://github.com/girliemac/a-picture-is-worth-a-1000-words/tree/main/ml/tiff).