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a/translations/da/1-Introduction/1-intro-to-ML/README.md +++ b/translations/da/1-Introduction/1-intro-to-ML/README.md @@ -1,12 +1,3 @@ - # Introduktion til maskinlæring ## [Quiz før lektionen](https://ff-quizzes.netlify.app/en/ml/) diff --git a/translations/da/1-Introduction/1-intro-to-ML/assignment.md b/translations/da/1-Introduction/1-intro-to-ML/assignment.md index d4e122ad2..a953a83e5 100644 --- a/translations/da/1-Introduction/1-intro-to-ML/assignment.md +++ b/translations/da/1-Introduction/1-intro-to-ML/assignment.md @@ -1,12 +1,3 @@ - # Kom i gang ## Instruktioner diff --git a/translations/da/1-Introduction/2-history-of-ML/README.md b/translations/da/1-Introduction/2-history-of-ML/README.md index 75bcc83e0..eb6c42eab 100644 --- a/translations/da/1-Introduction/2-history-of-ML/README.md +++ b/translations/da/1-Introduction/2-history-of-ML/README.md @@ -1,12 +1,3 @@ - # Historien om maskinlæring ![Oversigt over historien om maskinlæring i en sketchnote](../../../../sketchnotes/ml-history.png) diff --git a/translations/da/1-Introduction/2-history-of-ML/assignment.md b/translations/da/1-Introduction/2-history-of-ML/assignment.md index a3d8cab6c..49eb65069 100644 --- a/translations/da/1-Introduction/2-history-of-ML/assignment.md +++ b/translations/da/1-Introduction/2-history-of-ML/assignment.md @@ -1,12 +1,3 @@ - # Opret en tidslinje ## Instruktioner diff --git a/translations/da/1-Introduction/3-fairness/README.md b/translations/da/1-Introduction/3-fairness/README.md index 384c13b55..2f899e246 100644 --- a/translations/da/1-Introduction/3-fairness/README.md +++ b/translations/da/1-Introduction/3-fairness/README.md @@ -1,12 +1,3 @@ - # Bygge maskinlæringsløsninger med ansvarlig AI ![Oversigt over ansvarlig AI i maskinlæring i en sketchnote](../../../../sketchnotes/ml-fairness.png) diff --git a/translations/da/1-Introduction/3-fairness/assignment.md b/translations/da/1-Introduction/3-fairness/assignment.md index 0b8c19398..18eae86f9 100644 --- a/translations/da/1-Introduction/3-fairness/assignment.md +++ b/translations/da/1-Introduction/3-fairness/assignment.md @@ -1,12 +1,3 @@ - # Udforsk Responsible AI Toolbox ## Instruktioner diff --git a/translations/da/1-Introduction/4-techniques-of-ML/README.md b/translations/da/1-Introduction/4-techniques-of-ML/README.md index 11687b8be..0753b97a5 100644 --- a/translations/da/1-Introduction/4-techniques-of-ML/README.md +++ b/translations/da/1-Introduction/4-techniques-of-ML/README.md @@ -1,12 +1,3 @@ - # Teknikker inden for maskinlæring Processen med at opbygge, bruge og vedligeholde maskinlæringsmodeller og de data, de anvender, adskiller sig markant fra mange andre udviklingsarbejdsgange. I denne lektion vil vi afmystificere processen og skitsere de vigtigste teknikker, du skal kende. Du vil: diff --git a/translations/da/1-Introduction/4-techniques-of-ML/assignment.md b/translations/da/1-Introduction/4-techniques-of-ML/assignment.md index 3a205aaa4..1194979a6 100644 --- a/translations/da/1-Introduction/4-techniques-of-ML/assignment.md +++ b/translations/da/1-Introduction/4-techniques-of-ML/assignment.md @@ -1,12 +1,3 @@ - # Interview en data scientist ## Instruktioner diff --git a/translations/da/1-Introduction/README.md b/translations/da/1-Introduction/README.md index 4dc280431..865e91941 100644 --- a/translations/da/1-Introduction/README.md +++ b/translations/da/1-Introduction/README.md @@ -1,12 +1,3 @@ - # Introduktion til maskinlæring I denne del af pensum vil du blive introduceret til de grundlæggende begreber inden for maskinlæring, hvad det er, og lære om dets historie samt de teknikker, forskere bruger til at arbejde med det. Lad os udforske denne nye verden af ML sammen! diff --git a/translations/da/2-Regression/1-Tools/README.md b/translations/da/2-Regression/1-Tools/README.md index a37c09270..f284ff24e 100644 --- a/translations/da/2-Regression/1-Tools/README.md +++ b/translations/da/2-Regression/1-Tools/README.md @@ -1,12 +1,3 @@ - # Kom godt i gang med Python og Scikit-learn til regressionsmodeller ![Oversigt over regressioner i en sketchnote](../../../../sketchnotes/ml-regression.png) diff --git a/translations/da/2-Regression/1-Tools/assignment.md b/translations/da/2-Regression/1-Tools/assignment.md index 53d957d75..384d7b418 100644 --- a/translations/da/2-Regression/1-Tools/assignment.md +++ b/translations/da/2-Regression/1-Tools/assignment.md @@ -1,12 +1,3 @@ - # Regression med Scikit-learn ## Instruktioner diff --git a/translations/da/2-Regression/1-Tools/solution/Julia/README.md b/translations/da/2-Regression/1-Tools/solution/Julia/README.md index 9f393dc26..d595c225c 100644 --- a/translations/da/2-Regression/1-Tools/solution/Julia/README.md +++ b/translations/da/2-Regression/1-Tools/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/da/2-Regression/2-Data/README.md b/translations/da/2-Regression/2-Data/README.md index 27cee6573..ae83ebcef 100644 --- a/translations/da/2-Regression/2-Data/README.md +++ b/translations/da/2-Regression/2-Data/README.md @@ -1,12 +1,3 @@ - # Byg en regressionsmodel med Scikit-learn: forbered og visualiser data ![Data visualisering infographic](../../../../2-Regression/2-Data/images/data-visualization.png) diff --git a/translations/da/2-Regression/2-Data/assignment.md b/translations/da/2-Regression/2-Data/assignment.md index 17b4200b1..3f9a76fce 100644 --- a/translations/da/2-Regression/2-Data/assignment.md +++ b/translations/da/2-Regression/2-Data/assignment.md @@ -1,12 +1,3 @@ - # Udforskning af Visualiseringer Der findes flere forskellige biblioteker til datavisualisering. Lav nogle visualiseringer ved hjælp af Græskar-dataene i denne lektion med matplotlib og seaborn i en prøve-notebook. Hvilke biblioteker er nemmest at arbejde med? diff --git a/translations/da/2-Regression/2-Data/solution/Julia/README.md b/translations/da/2-Regression/2-Data/solution/Julia/README.md index d4fdfdef6..6c02d26af 100644 --- a/translations/da/2-Regression/2-Data/solution/Julia/README.md +++ b/translations/da/2-Regression/2-Data/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/da/2-Regression/3-Linear/README.md b/translations/da/2-Regression/3-Linear/README.md index 40b165d43..3a80d7a3c 100644 --- a/translations/da/2-Regression/3-Linear/README.md +++ b/translations/da/2-Regression/3-Linear/README.md @@ -1,12 +1,3 @@ - # Byg en regressionsmodel med Scikit-learn: regression på fire måder ![Infografik om lineær vs. polynomisk regression](../../../../2-Regression/3-Linear/images/linear-polynomial.png) @@ -114,11 +105,11 @@ Nu hvor du har en forståelse af matematikken bag lineær regression, lad os opr Fra den forrige lektion har du sandsynligvis set, at gennemsnitsprisen for forskellige måneder ser sådan ud: -Gennemsnitspris pr. måned +Gennemsnitspris pr. måned Dette antyder, at der bør være en vis korrelation, og vi kan prøve at træne en lineær regressionsmodel til at forudsige forholdet mellem `Month` og `Price`, eller mellem `DayOfYear` og `Price`. Her er scatterplottet, der viser sidstnævnte forhold: -Scatterplot af pris vs. dag i året +Scatterplot af pris vs. dag i året Lad os se, om der er en korrelation ved hjælp af funktionen `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) ``` -Scatterplot af pris vs. dag i året +Scatterplot af pris vs. dag i året Vores undersøgelse antyder, at sorten har større effekt på den samlede pris end den faktiske salgsdato. Vi kan se dette med et søjlediagram: @@ -145,7 +136,7 @@ Vores undersøgelse antyder, at sorten har større effekt på den samlede pris e new_pumpkins.groupby('Variety')['Price'].mean().plot(kind='bar') ``` -Søjlediagram af pris vs. sort +Søjlediagram af pris vs. sort Lad os fokusere for øjeblikket kun på én græskarsort, 'pie type', og se, hvilken effekt datoen har på prisen: @@ -153,7 +144,7 @@ Lad os fokusere for øjeblikket kun på én græskarsort, 'pie type', og se, hvi pie_pumpkins = new_pumpkins[new_pumpkins['Variety']=='PIE TYPE'] pie_pumpkins.plot.scatter('DayOfYear','Price') ``` -Scatterplot af pris vs. dag i året +Scatterplot af pris vs. dag i året Hvis vi nu beregner korrelationen mellem `Price` og `DayOfYear` ved hjælp af funktionen `corr`, får vi noget som `-0.27` - hvilket betyder, at det giver mening at træne en forudsigelsesmodel. @@ -227,7 +218,7 @@ plt.scatter(X_test,y_test) plt.plot(X_test,pred) ``` -Lineær regression +Lineær regression ## Polynomisk Regression @@ -256,7 +247,7 @@ Ved at bruge `PolynomialFeatures(2)` betyder det, at vi vil inkludere alle anden Pipelines kan bruges på samme måde som det originale `LinearRegression`-objekt, dvs. vi kan `fit` pipelinen og derefter bruge `predict` til at få forudsigelsesresultater. Her er grafen, der viser testdata og tilnærmningskurven: -Polynomisk regression +Polynomisk regression Ved at bruge polynomisk regression kan vi få en lidt lavere MSE og højere bestemmelseskoefficient, men ikke markant. Vi skal tage andre funktioner i betragtning! @@ -274,7 +265,7 @@ I en ideel verden ønsker vi at kunne forudsige priser for forskellige græskars Her kan du se, hvordan gennemsnitsprisen afhænger af sorten: -Gennemsnitspris efter sort +Gennemsnitspris efter sort For at tage sorten i betragtning skal vi først konvertere den til numerisk form, eller **kode** den. Der er flere måder, vi kan gøre det på: diff --git a/translations/da/2-Regression/3-Linear/assignment.md b/translations/da/2-Regression/3-Linear/assignment.md index 8302f0849..2ba7eabb7 100644 --- a/translations/da/2-Regression/3-Linear/assignment.md +++ b/translations/da/2-Regression/3-Linear/assignment.md @@ -1,12 +1,3 @@ - # Opret en regressionsmodel ## Instruktioner diff --git a/translations/da/2-Regression/3-Linear/solution/Julia/README.md b/translations/da/2-Regression/3-Linear/solution/Julia/README.md index 8bc1bb530..90399033c 100644 --- a/translations/da/2-Regression/3-Linear/solution/Julia/README.md +++ b/translations/da/2-Regression/3-Linear/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/da/2-Regression/4-Logistic/README.md b/translations/da/2-Regression/4-Logistic/README.md index e56c580e3..1b55ba226 100644 --- a/translations/da/2-Regression/4-Logistic/README.md +++ b/translations/da/2-Regression/4-Logistic/README.md @@ -1,12 +1,3 @@ - # Logistisk regression til at forudsige kategorier ![Infografik om logistisk vs. lineær regression](../../../../2-Regression/4-Logistic/images/linear-vs-logistic.png) diff --git a/translations/da/2-Regression/4-Logistic/assignment.md b/translations/da/2-Regression/4-Logistic/assignment.md index eaf5d64b9..fb2ccc264 100644 --- a/translations/da/2-Regression/4-Logistic/assignment.md +++ b/translations/da/2-Regression/4-Logistic/assignment.md @@ -1,12 +1,3 @@ - # Gentagelse af noget Regression ## Instruktioner diff --git a/translations/da/2-Regression/4-Logistic/solution/Julia/README.md b/translations/da/2-Regression/4-Logistic/solution/Julia/README.md index d29e0c53f..d595c225c 100644 --- a/translations/da/2-Regression/4-Logistic/solution/Julia/README.md +++ b/translations/da/2-Regression/4-Logistic/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/da/2-Regression/README.md b/translations/da/2-Regression/README.md index c81902467..c6fe1d5a7 100644 --- a/translations/da/2-Regression/README.md +++ b/translations/da/2-Regression/README.md @@ -1,12 +1,3 @@ - # Regressionsmodeller for maskinlæring ## Regionalt emne: Regressionsmodeller for græskarpriser i Nordamerika 🎃 diff --git a/translations/da/3-Web-App/1-Web-App/README.md b/translations/da/3-Web-App/1-Web-App/README.md index 152b55fc3..454684e47 100644 --- a/translations/da/3-Web-App/1-Web-App/README.md +++ b/translations/da/3-Web-App/1-Web-App/README.md @@ -1,12 +1,3 @@ - # Byg en webapp til at bruge en ML-model I denne lektion vil du træne en ML-model på et datasæt, der er helt ude af denne verden: _UFO-observationer over det sidste århundrede_, hentet fra NUFORC's database. diff --git a/translations/da/3-Web-App/1-Web-App/assignment.md b/translations/da/3-Web-App/1-Web-App/assignment.md index 33e69b193..dca22efdb 100644 --- a/translations/da/3-Web-App/1-Web-App/assignment.md +++ b/translations/da/3-Web-App/1-Web-App/assignment.md @@ -1,12 +1,3 @@ - # Prøv en anden model ## Instruktioner diff --git a/translations/da/3-Web-App/README.md b/translations/da/3-Web-App/README.md index f1fba0fb0..ab1f881d7 100644 --- a/translations/da/3-Web-App/README.md +++ b/translations/da/3-Web-App/README.md @@ -1,12 +1,3 @@ - # Byg en webapp til at bruge din ML-model I denne del af pensum vil du blive introduceret til et anvendt ML-emne: hvordan du gemmer din Scikit-learn-model som en fil, der kan bruges til at lave forudsigelser i en webapplikation. Når modellen er gemt, lærer du, hvordan du bruger den i en webapp bygget i Flask. Først opretter du en model ved hjælp af nogle data, der handler om UFO-observationer! Derefter bygger du en webapp, der giver dig mulighed for at indtaste et antal sekunder sammen med en bredde- og længdegradsværdi for at forudsige, hvilket land der rapporterede at have set en UFO. diff --git a/translations/da/4-Classification/1-Introduction/README.md b/translations/da/4-Classification/1-Introduction/README.md index fa1e05e9c..9933c1d76 100644 --- a/translations/da/4-Classification/1-Introduction/README.md +++ b/translations/da/4-Classification/1-Introduction/README.md @@ -1,12 +1,3 @@ - # Introduktion til klassifikation I disse fire lektioner vil du udforske et grundlæggende fokusområde inden for klassisk maskinlæring - _klassifikation_. Vi vil gennemgå brugen af forskellige klassifikationsalgoritmer med et datasæt om alle de fantastiske køkkener fra Asien og Indien. Håber du er sulten! diff --git a/translations/da/4-Classification/1-Introduction/assignment.md b/translations/da/4-Classification/1-Introduction/assignment.md index a11188b6f..520240120 100644 --- a/translations/da/4-Classification/1-Introduction/assignment.md +++ b/translations/da/4-Classification/1-Introduction/assignment.md @@ -1,12 +1,3 @@ - # Udforsk klassifikationsmetoder ## Instruktioner diff --git a/translations/da/4-Classification/1-Introduction/solution/Julia/README.md b/translations/da/4-Classification/1-Introduction/solution/Julia/README.md index b463d1495..90399033c 100644 --- a/translations/da/4-Classification/1-Introduction/solution/Julia/README.md +++ b/translations/da/4-Classification/1-Introduction/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/da/4-Classification/2-Classifiers-1/README.md b/translations/da/4-Classification/2-Classifiers-1/README.md index 36fb6598f..c3d079f9f 100644 --- a/translations/da/4-Classification/2-Classifiers-1/README.md +++ b/translations/da/4-Classification/2-Classifiers-1/README.md @@ -1,12 +1,3 @@ - # Klassifikatorer for køkkener 1 I denne lektion vil du bruge det datasæt, du gemte fra den sidste lektion, fyldt med balancerede og rene data om køkkener. diff --git a/translations/da/4-Classification/2-Classifiers-1/assignment.md b/translations/da/4-Classification/2-Classifiers-1/assignment.md index 936511ad9..1c64bd942 100644 --- a/translations/da/4-Classification/2-Classifiers-1/assignment.md +++ b/translations/da/4-Classification/2-Classifiers-1/assignment.md @@ -1,12 +1,3 @@ - # Undersøg løserne ## Instruktioner diff --git a/translations/da/4-Classification/2-Classifiers-1/solution/Julia/README.md b/translations/da/4-Classification/2-Classifiers-1/solution/Julia/README.md index ec1880789..e1c447afd 100644 --- a/translations/da/4-Classification/2-Classifiers-1/solution/Julia/README.md +++ b/translations/da/4-Classification/2-Classifiers-1/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/da/4-Classification/3-Classifiers-2/README.md b/translations/da/4-Classification/3-Classifiers-2/README.md index 8d745b530..c7a2be73d 100644 --- a/translations/da/4-Classification/3-Classifiers-2/README.md +++ b/translations/da/4-Classification/3-Classifiers-2/README.md @@ -1,12 +1,3 @@ - # Klassifikatorer for køkken 2 I denne anden lektion om klassifikation vil du udforske flere måder at klassificere numeriske data på. Du vil også lære om konsekvenserne ved at vælge én klassifikator frem for en anden. diff --git a/translations/da/4-Classification/3-Classifiers-2/assignment.md b/translations/da/4-Classification/3-Classifiers-2/assignment.md index 24c52876a..4c8e6eb32 100644 --- a/translations/da/4-Classification/3-Classifiers-2/assignment.md +++ b/translations/da/4-Classification/3-Classifiers-2/assignment.md @@ -1,12 +1,3 @@ - # Parameterleg ## Instruktioner diff --git a/translations/da/4-Classification/3-Classifiers-2/solution/Julia/README.md b/translations/da/4-Classification/3-Classifiers-2/solution/Julia/README.md index ce8e4f54c..ec4f25cfe 100644 --- a/translations/da/4-Classification/3-Classifiers-2/solution/Julia/README.md +++ b/translations/da/4-Classification/3-Classifiers-2/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/da/4-Classification/4-Applied/README.md b/translations/da/4-Classification/4-Applied/README.md index f80294b58..dee06fd29 100644 --- a/translations/da/4-Classification/4-Applied/README.md +++ b/translations/da/4-Classification/4-Applied/README.md @@ -1,12 +1,3 @@ - # Byg en webapp til anbefaling af køkkener I denne lektion vil du bygge en klassifikationsmodel ved hjælp af nogle af de teknikker, du har lært i tidligere lektioner, og med det lækre køkkendatasæt, der er blevet brugt gennem hele denne serie. Derudover vil du bygge en lille webapp til at bruge en gemt model, der udnytter Onnx's web-runtime. diff --git a/translations/da/4-Classification/4-Applied/assignment.md b/translations/da/4-Classification/4-Applied/assignment.md index e2d0dcdd8..34a6bb91e 100644 --- a/translations/da/4-Classification/4-Applied/assignment.md +++ b/translations/da/4-Classification/4-Applied/assignment.md @@ -1,12 +1,3 @@ - # Byg en anbefalingsmotor ## Instruktioner diff --git a/translations/da/4-Classification/README.md b/translations/da/4-Classification/README.md index e7cde23dc..de6644c3d 100644 --- a/translations/da/4-Classification/README.md +++ b/translations/da/4-Classification/README.md @@ -1,12 +1,3 @@ - # Kom godt i gang med klassifikation ## Regionalt emne: Lækre asiatiske og indiske køkkener 🍜 diff --git a/translations/da/5-Clustering/1-Visualize/README.md b/translations/da/5-Clustering/1-Visualize/README.md index c6ad71036..d07307d6d 100644 --- a/translations/da/5-Clustering/1-Visualize/README.md +++ b/translations/da/5-Clustering/1-Visualize/README.md @@ -1,12 +1,3 @@ - # Introduktion til clustering Clustering er en type [Unsupervised Learning](https://wikipedia.org/wiki/Unsupervised_learning), der antager, at et datasæt er ulabeleret, eller at dets input ikke er matchet med foruddefinerede output. Det bruger forskellige algoritmer til at sortere gennem ulabeleret data og levere grupperinger baseret på mønstre, det identificerer i dataene. diff --git a/translations/da/5-Clustering/1-Visualize/assignment.md b/translations/da/5-Clustering/1-Visualize/assignment.md index b29e3a9cc..4e156e885 100644 --- a/translations/da/5-Clustering/1-Visualize/assignment.md +++ b/translations/da/5-Clustering/1-Visualize/assignment.md @@ -1,12 +1,3 @@ - # Undersøg andre visualiseringer for klyngedannelse ## Instruktioner diff --git a/translations/da/5-Clustering/1-Visualize/solution/Julia/README.md b/translations/da/5-Clustering/1-Visualize/solution/Julia/README.md index e031ec52a..90399033c 100644 --- a/translations/da/5-Clustering/1-Visualize/solution/Julia/README.md +++ b/translations/da/5-Clustering/1-Visualize/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/da/5-Clustering/2-K-Means/README.md b/translations/da/5-Clustering/2-K-Means/README.md index a5eb6aebc..ab4594b1a 100644 --- a/translations/da/5-Clustering/2-K-Means/README.md +++ b/translations/da/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/da/5-Clustering/2-K-Means/assignment.md b/translations/da/5-Clustering/2-K-Means/assignment.md index 72f752b5d..59f1eb90c 100644 --- a/translations/da/5-Clustering/2-K-Means/assignment.md +++ b/translations/da/5-Clustering/2-K-Means/assignment.md @@ -1,12 +1,3 @@ - # Prøv forskellige klyngemetoder ## Instruktioner diff --git a/translations/da/5-Clustering/2-K-Means/solution/Julia/README.md b/translations/da/5-Clustering/2-K-Means/solution/Julia/README.md index 1748f93a5..ec4f25cfe 100644 --- a/translations/da/5-Clustering/2-K-Means/solution/Julia/README.md +++ b/translations/da/5-Clustering/2-K-Means/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/da/5-Clustering/README.md b/translations/da/5-Clustering/README.md index 834f29273..ee3df1f1e 100644 --- a/translations/da/5-Clustering/README.md +++ b/translations/da/5-Clustering/README.md @@ -1,12 +1,3 @@ - # Klyngemodeller til maskinlæring Klyngedannelse er en maskinlæringsopgave, hvor man forsøger at finde objekter, der ligner hinanden, og gruppere dem i grupper kaldet klynger. Det, der adskiller klyngedannelse fra andre tilgange inden for maskinlæring, er, at processen sker automatisk. Faktisk kan man sige, at det er det modsatte af superviseret læring. diff --git a/translations/da/6-NLP/1-Introduction-to-NLP/README.md b/translations/da/6-NLP/1-Introduction-to-NLP/README.md index 722fa50cc..079246d82 100644 --- a/translations/da/6-NLP/1-Introduction-to-NLP/README.md +++ b/translations/da/6-NLP/1-Introduction-to-NLP/README.md @@ -1,12 +1,3 @@ - # Introduktion til naturlig sprogbehandling Denne lektion dækker en kort historie og vigtige begreber inden for *naturlig sprogbehandling*, et underfelt af *computational linguistics*. diff --git a/translations/da/6-NLP/1-Introduction-to-NLP/assignment.md b/translations/da/6-NLP/1-Introduction-to-NLP/assignment.md index 52ca81374..2366a734b 100644 --- a/translations/da/6-NLP/1-Introduction-to-NLP/assignment.md +++ b/translations/da/6-NLP/1-Introduction-to-NLP/assignment.md @@ -1,12 +1,3 @@ - # Søg efter en bot ## Instruktioner diff --git a/translations/da/6-NLP/2-Tasks/README.md b/translations/da/6-NLP/2-Tasks/README.md index 120d149f3..c94d62c6d 100644 --- a/translations/da/6-NLP/2-Tasks/README.md +++ b/translations/da/6-NLP/2-Tasks/README.md @@ -1,12 +1,3 @@ - # Almindelige opgaver og teknikker inden for naturlig sprogbehandling For de fleste *naturlig sprogbehandling*-opgaver skal teksten, der skal behandles, opdeles, analyseres, og resultaterne gemmes eller krydsrefereres med regler og datasæt. Disse opgaver gør det muligt for programmøren at udlede _betydningen_ eller _intentionen_ eller blot _frekvensen_ af termer og ord i en tekst. diff --git a/translations/da/6-NLP/2-Tasks/assignment.md b/translations/da/6-NLP/2-Tasks/assignment.md index 4fa831797..cc98d5c97 100644 --- a/translations/da/6-NLP/2-Tasks/assignment.md +++ b/translations/da/6-NLP/2-Tasks/assignment.md @@ -1,12 +1,3 @@ - # Få en bot til at svare tilbage ## Instruktioner diff --git a/translations/da/6-NLP/3-Translation-Sentiment/README.md b/translations/da/6-NLP/3-Translation-Sentiment/README.md index c863e6bab..b12f1ba41 100644 --- a/translations/da/6-NLP/3-Translation-Sentiment/README.md +++ b/translations/da/6-NLP/3-Translation-Sentiment/README.md @@ -1,12 +1,3 @@ - # Oversættelse og sentimentanalyse med ML I de tidligere lektioner lærte du, hvordan man bygger en grundlæggende bot ved hjælp af `TextBlob`, et bibliotek, der integrerer ML bag kulisserne for at udføre grundlæggende NLP-opgaver som udtrækning af navneordssætninger. En anden vigtig udfordring inden for computerlingvistik er præcis _oversættelse_ af en sætning fra et talesprog eller skriftsprog til et andet. diff --git a/translations/da/6-NLP/3-Translation-Sentiment/assignment.md b/translations/da/6-NLP/3-Translation-Sentiment/assignment.md index 21643ed14..0ca44d814 100644 --- a/translations/da/6-NLP/3-Translation-Sentiment/assignment.md +++ b/translations/da/6-NLP/3-Translation-Sentiment/assignment.md @@ -1,12 +1,3 @@ - # Poetisk frihed ## Instruktioner diff --git a/translations/da/6-NLP/3-Translation-Sentiment/solution/Julia/README.md b/translations/da/6-NLP/3-Translation-Sentiment/solution/Julia/README.md index c1968697d..90399033c 100644 --- a/translations/da/6-NLP/3-Translation-Sentiment/solution/Julia/README.md +++ b/translations/da/6-NLP/3-Translation-Sentiment/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/da/6-NLP/3-Translation-Sentiment/solution/R/README.md b/translations/da/6-NLP/3-Translation-Sentiment/solution/R/README.md index 66c5db855..77621c617 100644 --- a/translations/da/6-NLP/3-Translation-Sentiment/solution/R/README.md +++ b/translations/da/6-NLP/3-Translation-Sentiment/solution/R/README.md @@ -1,12 +1,3 @@ - dette er en midlertidig pladsholder --- diff --git a/translations/da/6-NLP/4-Hotel-Reviews-1/README.md b/translations/da/6-NLP/4-Hotel-Reviews-1/README.md index 7d3fc66b8..fb0b2e350 100644 --- a/translations/da/6-NLP/4-Hotel-Reviews-1/README.md +++ b/translations/da/6-NLP/4-Hotel-Reviews-1/README.md @@ -1,12 +1,3 @@ - # Sentimentanalyse med hotelanmeldelser - bearbejdning af data I denne sektion vil du bruge teknikkerne fra de tidligere lektioner til at lave en udforskende dataanalyse af et stort datasæt. Når du har fået en god forståelse af nytten af de forskellige kolonner, vil du lære: diff --git a/translations/da/6-NLP/4-Hotel-Reviews-1/assignment.md b/translations/da/6-NLP/4-Hotel-Reviews-1/assignment.md index 3df3b6b96..a05f19c2f 100644 --- a/translations/da/6-NLP/4-Hotel-Reviews-1/assignment.md +++ b/translations/da/6-NLP/4-Hotel-Reviews-1/assignment.md @@ -1,12 +1,3 @@ - # NLTK ## Instruktioner diff --git a/translations/da/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md b/translations/da/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md index 9dacd0f27..d595c225c 100644 --- a/translations/da/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md +++ b/translations/da/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/da/6-NLP/4-Hotel-Reviews-1/solution/R/README.md b/translations/da/6-NLP/4-Hotel-Reviews-1/solution/R/README.md index 9443a21c2..e53544277 100644 --- a/translations/da/6-NLP/4-Hotel-Reviews-1/solution/R/README.md +++ b/translations/da/6-NLP/4-Hotel-Reviews-1/solution/R/README.md @@ -1,12 +1,3 @@ - dette er en midlertidig pladsholder --- diff --git a/translations/da/6-NLP/5-Hotel-Reviews-2/README.md b/translations/da/6-NLP/5-Hotel-Reviews-2/README.md index b42caa36c..a217d32a0 100644 --- a/translations/da/6-NLP/5-Hotel-Reviews-2/README.md +++ b/translations/da/6-NLP/5-Hotel-Reviews-2/README.md @@ -1,12 +1,3 @@ - # Sentimentanalyse med hotelanmeldelser Nu hvor du har udforsket datasættet i detaljer, er det tid til at filtrere kolonnerne og derefter bruge NLP-teknikker på datasættet for at få nye indsigter om hotellerne. diff --git a/translations/da/6-NLP/5-Hotel-Reviews-2/assignment.md b/translations/da/6-NLP/5-Hotel-Reviews-2/assignment.md index 88e1c3fea..380b06a63 100644 --- a/translations/da/6-NLP/5-Hotel-Reviews-2/assignment.md +++ b/translations/da/6-NLP/5-Hotel-Reviews-2/assignment.md @@ -1,12 +1,3 @@ - # Prøv et andet datasæt ## Instruktioner diff --git a/translations/da/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md b/translations/da/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md index d8a1c8cf7..fbbdd6cc4 100644 --- a/translations/da/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md +++ b/translations/da/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/da/6-NLP/5-Hotel-Reviews-2/solution/R/README.md b/translations/da/6-NLP/5-Hotel-Reviews-2/solution/R/README.md index 0c7eb8a01..5310fd9fb 100644 --- a/translations/da/6-NLP/5-Hotel-Reviews-2/solution/R/README.md +++ b/translations/da/6-NLP/5-Hotel-Reviews-2/solution/R/README.md @@ -1,12 +1,3 @@ - dette er en midlertidig pladsholder --- diff --git a/translations/da/6-NLP/README.md b/translations/da/6-NLP/README.md index 71b13446c..a6851becf 100644 --- a/translations/da/6-NLP/README.md +++ b/translations/da/6-NLP/README.md @@ -1,12 +1,3 @@ - # Kom godt i gang med naturlig sprogbehandling Naturlig sprogbehandling (NLP) er evnen for et computerprogram til at forstå menneskeligt sprog, som det tales og skrives – kaldet naturligt sprog. Det er en komponent af kunstig intelligens (AI). NLP har eksisteret i mere end 50 år og har rødder i lingvistik. Hele området er rettet mod at hjælpe maskiner med at forstå og bearbejde menneskeligt sprog. Dette kan derefter bruges til at udføre opgaver som stavekontrol eller maskinoversættelse. Det har en række praktiske anvendelser inden for flere områder, herunder medicinsk forskning, søgemaskiner og forretningsanalyse. diff --git a/translations/da/6-NLP/data/README.md b/translations/da/6-NLP/data/README.md index f9b50150d..86c490672 100644 --- a/translations/da/6-NLP/data/README.md +++ b/translations/da/6-NLP/data/README.md @@ -1,12 +1,3 @@ - Download hotelanmeldelsesdataene til denne mappe. --- diff --git a/translations/da/7-TimeSeries/1-Introduction/README.md b/translations/da/7-TimeSeries/1-Introduction/README.md index ec0c97e3b..80af68897 100644 --- a/translations/da/7-TimeSeries/1-Introduction/README.md +++ b/translations/da/7-TimeSeries/1-Introduction/README.md @@ -1,12 +1,3 @@ - # Introduktion til tidsserieforudsigelse ![Oversigt over tidsserier i en sketchnote](../../../../sketchnotes/ml-timeseries.png) diff --git a/translations/da/7-TimeSeries/1-Introduction/assignment.md b/translations/da/7-TimeSeries/1-Introduction/assignment.md index d976e3f68..d680ed404 100644 --- a/translations/da/7-TimeSeries/1-Introduction/assignment.md +++ b/translations/da/7-TimeSeries/1-Introduction/assignment.md @@ -1,12 +1,3 @@ - # Visualiser nogle flere tidsserier ## Instruktioner diff --git a/translations/da/7-TimeSeries/1-Introduction/solution/Julia/README.md b/translations/da/7-TimeSeries/1-Introduction/solution/Julia/README.md index 058c8f40f..90399033c 100644 --- a/translations/da/7-TimeSeries/1-Introduction/solution/Julia/README.md +++ b/translations/da/7-TimeSeries/1-Introduction/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/da/7-TimeSeries/1-Introduction/solution/R/README.md b/translations/da/7-TimeSeries/1-Introduction/solution/R/README.md index 114d8f684..77621c617 100644 --- a/translations/da/7-TimeSeries/1-Introduction/solution/R/README.md +++ b/translations/da/7-TimeSeries/1-Introduction/solution/R/README.md @@ -1,12 +1,3 @@ - dette er en midlertidig pladsholder --- diff --git a/translations/da/7-TimeSeries/2-ARIMA/README.md b/translations/da/7-TimeSeries/2-ARIMA/README.md index 33feeb2e1..1a89c1087 100644 --- a/translations/da/7-TimeSeries/2-ARIMA/README.md +++ b/translations/da/7-TimeSeries/2-ARIMA/README.md @@ -1,12 +1,3 @@ - # Tidsserieprognoser med ARIMA I den forrige lektion lærte du lidt om tidsserieprognoser og indlæste et datasæt, der viser udsving i elektrisk belastning over en tidsperiode. diff --git a/translations/da/7-TimeSeries/2-ARIMA/assignment.md b/translations/da/7-TimeSeries/2-ARIMA/assignment.md index d5948b490..dbfdd7df4 100644 --- a/translations/da/7-TimeSeries/2-ARIMA/assignment.md +++ b/translations/da/7-TimeSeries/2-ARIMA/assignment.md @@ -1,12 +1,3 @@ - # En ny ARIMA-model ## Instruktioner diff --git a/translations/da/7-TimeSeries/2-ARIMA/solution/Julia/README.md b/translations/da/7-TimeSeries/2-ARIMA/solution/Julia/README.md index 64b70bc5a..b15c081aa 100644 --- a/translations/da/7-TimeSeries/2-ARIMA/solution/Julia/README.md +++ b/translations/da/7-TimeSeries/2-ARIMA/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/da/7-TimeSeries/2-ARIMA/solution/R/README.md b/translations/da/7-TimeSeries/2-ARIMA/solution/R/README.md index 5fdb3a5c4..e53544277 100644 --- a/translations/da/7-TimeSeries/2-ARIMA/solution/R/README.md +++ b/translations/da/7-TimeSeries/2-ARIMA/solution/R/README.md @@ -1,12 +1,3 @@ - dette er en midlertidig pladsholder --- diff --git a/translations/da/7-TimeSeries/3-SVR/README.md b/translations/da/7-TimeSeries/3-SVR/README.md index e5bb4ea20..bcf1daa04 100644 --- a/translations/da/7-TimeSeries/3-SVR/README.md +++ b/translations/da/7-TimeSeries/3-SVR/README.md @@ -1,12 +1,3 @@ - # Tidsserieforudsigelse med Support Vector Regressor I den forrige lektion lærte du, hvordan man bruger ARIMA-modellen til at lave tidsserieforudsigelser. Nu skal du se på Support Vector Regressor-modellen, som er en regressionsmodel, der bruges til at forudsige kontinuerlige data. diff --git a/translations/da/7-TimeSeries/3-SVR/assignment.md b/translations/da/7-TimeSeries/3-SVR/assignment.md index 2eaab547e..2582c1302 100644 --- a/translations/da/7-TimeSeries/3-SVR/assignment.md +++ b/translations/da/7-TimeSeries/3-SVR/assignment.md @@ -1,12 +1,3 @@ - # En ny SVR-model ## Instruktioner [^1] diff --git a/translations/da/7-TimeSeries/README.md b/translations/da/7-TimeSeries/README.md index 3f6887667..d57c4e9bf 100644 --- a/translations/da/7-TimeSeries/README.md +++ b/translations/da/7-TimeSeries/README.md @@ -1,12 +1,3 @@ - # Introduktion til tidsserieforudsigelse Hvad er tidsserieforudsigelse? Det handler om at forudsige fremtidige begivenheder ved at analysere tidligere tendenser. diff --git a/translations/da/8-Reinforcement/1-QLearning/README.md b/translations/da/8-Reinforcement/1-QLearning/README.md index 774da9a16..7d627851d 100644 --- a/translations/da/8-Reinforcement/1-QLearning/README.md +++ b/translations/da/8-Reinforcement/1-QLearning/README.md @@ -1,12 +1,3 @@ - # Introduktion til Forstærkningslæring og Q-Learning ![Oversigt over forstærkning i maskinlæring i en sketchnote](../../../../sketchnotes/ml-reinforcement.png) diff --git a/translations/da/8-Reinforcement/1-QLearning/assignment.md b/translations/da/8-Reinforcement/1-QLearning/assignment.md index 9acc78bb1..ab77ba1bf 100644 --- a/translations/da/8-Reinforcement/1-QLearning/assignment.md +++ b/translations/da/8-Reinforcement/1-QLearning/assignment.md @@ -1,12 +1,3 @@ - # En Mere Realistisk Verden I vores situation kunne Peter bevæge sig rundt næsten uden at blive træt eller sulten. I en mere realistisk verden skal han sætte sig ned og hvile fra tid til anden og også sørge for at spise. Lad os gøre vores verden mere realistisk ved at implementere følgende regler: diff --git a/translations/da/8-Reinforcement/1-QLearning/solution/Julia/README.md b/translations/da/8-Reinforcement/1-QLearning/solution/Julia/README.md index 98adb85e5..d595c225c 100644 --- a/translations/da/8-Reinforcement/1-QLearning/solution/Julia/README.md +++ b/translations/da/8-Reinforcement/1-QLearning/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/da/8-Reinforcement/1-QLearning/solution/R/README.md b/translations/da/8-Reinforcement/1-QLearning/solution/R/README.md index 831357f8f..db21f388c 100644 --- a/translations/da/8-Reinforcement/1-QLearning/solution/R/README.md +++ b/translations/da/8-Reinforcement/1-QLearning/solution/R/README.md @@ -1,12 +1,3 @@ - dette er en midlertidig pladsholder --- diff --git a/translations/da/8-Reinforcement/2-Gym/README.md b/translations/da/8-Reinforcement/2-Gym/README.md index fe5038caf..2a69df547 100644 --- a/translations/da/8-Reinforcement/2-Gym/README.md +++ b/translations/da/8-Reinforcement/2-Gym/README.md @@ -1,12 +1,3 @@ - # CartPole Skating Problemet, vi har arbejdet med i den tidligere lektion, kan virke som et legetøjsproblem, der ikke rigtig har relevans for virkelige scenarier. Dette er dog ikke tilfældet, da mange virkelige problemer deler samme karakteristika – herunder at spille skak eller Go. De er ens, fordi vi også har et bræt med givne regler og en **diskret tilstand**. diff --git a/translations/da/8-Reinforcement/2-Gym/assignment.md b/translations/da/8-Reinforcement/2-Gym/assignment.md index ae11e4fc0..652df39d0 100644 --- a/translations/da/8-Reinforcement/2-Gym/assignment.md +++ b/translations/da/8-Reinforcement/2-Gym/assignment.md @@ -1,12 +1,3 @@ - # Træn Mountain Car [OpenAI Gym](http://gym.openai.com) er designet på en måde, hvor alle miljøer tilbyder den samme API - dvs. de samme metoder `reset`, `step` og `render`, samt de samme abstraktioner af **aktionsrum** og **observationsrum**. Derfor bør det være muligt at tilpasse de samme forstærkningslæringsalgoritmer til forskellige miljøer med minimale kodeændringer. diff --git a/translations/da/8-Reinforcement/2-Gym/solution/Julia/README.md b/translations/da/8-Reinforcement/2-Gym/solution/Julia/README.md index 621e09cc1..52a383ce0 100644 --- a/translations/da/8-Reinforcement/2-Gym/solution/Julia/README.md +++ b/translations/da/8-Reinforcement/2-Gym/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/da/8-Reinforcement/2-Gym/solution/R/README.md b/translations/da/8-Reinforcement/2-Gym/solution/R/README.md index 446f4bb04..e53544277 100644 --- a/translations/da/8-Reinforcement/2-Gym/solution/R/README.md +++ b/translations/da/8-Reinforcement/2-Gym/solution/R/README.md @@ -1,12 +1,3 @@ - dette er en midlertidig pladsholder --- diff --git a/translations/da/8-Reinforcement/README.md b/translations/da/8-Reinforcement/README.md index 4f4da8170..de8be3b79 100644 --- a/translations/da/8-Reinforcement/README.md +++ b/translations/da/8-Reinforcement/README.md @@ -1,12 +1,3 @@ - # Introduktion til forstærkningslæring Forstærkningslæring, RL, betragtes som en af de grundlæggende paradigmer inden for maskinlæring, ved siden af superviseret læring og usuperviseret læring. RL handler om beslutninger: at træffe de rigtige beslutninger eller i det mindste lære af dem. diff --git a/translations/da/9-Real-World/1-Applications/README.md b/translations/da/9-Real-World/1-Applications/README.md index b606514f4..3301a52c5 100644 --- a/translations/da/9-Real-World/1-Applications/README.md +++ b/translations/da/9-Real-World/1-Applications/README.md @@ -1,12 +1,3 @@ - # Postscript: Maskinlæring i den virkelige verden ![Oversigt over maskinlæring i den virkelige verden i en sketchnote](../../../../sketchnotes/ml-realworld.png) diff --git a/translations/da/9-Real-World/1-Applications/assignment.md b/translations/da/9-Real-World/1-Applications/assignment.md index c15549a6f..b97470754 100644 --- a/translations/da/9-Real-World/1-Applications/assignment.md +++ b/translations/da/9-Real-World/1-Applications/assignment.md @@ -1,12 +1,3 @@ - # En ML Skattejagt ## Instruktioner diff --git a/translations/da/9-Real-World/2-Debugging-ML-Models/README.md b/translations/da/9-Real-World/2-Debugging-ML-Models/README.md index fc80c47d4..9362b29cf 100644 --- a/translations/da/9-Real-World/2-Debugging-ML-Models/README.md +++ b/translations/da/9-Real-World/2-Debugging-ML-Models/README.md @@ -1,12 +1,3 @@ - # Postscript: Model Debugging i Maskinlæring ved hjælp af komponenter fra Responsible AI-dashboardet ## [Pre-lecture quiz](https://ff-quizzes.netlify.app/en/ml/) diff --git a/translations/da/9-Real-World/2-Debugging-ML-Models/assignment.md b/translations/da/9-Real-World/2-Debugging-ML-Models/assignment.md index be8e6b43f..18007ca3c 100644 --- a/translations/da/9-Real-World/2-Debugging-ML-Models/assignment.md +++ b/translations/da/9-Real-World/2-Debugging-ML-Models/assignment.md @@ -1,12 +1,3 @@ - # Udforsk Responsible AI (RAI) dashboard ## Instruktioner diff --git a/translations/da/9-Real-World/README.md b/translations/da/9-Real-World/README.md index 6c07009c7..ef6c0a3dd 100644 --- a/translations/da/9-Real-World/README.md +++ b/translations/da/9-Real-World/README.md @@ -1,12 +1,3 @@ - # Postscript: Virkelige anvendelser af klassisk maskinlæring I denne del af pensum vil du blive introduceret til nogle virkelige anvendelser af klassisk maskinlæring. Vi har gennemsøgt internettet for at finde videnskabelige artikler og artikler om anvendelser, der har brugt disse strategier, og undgået neurale netværk, dyb læring og AI så meget som muligt. Lær om, hvordan maskinlæring bruges i forretningssystemer, økologiske anvendelser, finans, kunst og kultur og meget mere. diff --git a/translations/da/AGENTS.md b/translations/da/AGENTS.md index 77af0bac0..8f1e9ab62 100644 --- a/translations/da/AGENTS.md +++ b/translations/da/AGENTS.md @@ -1,12 +1,3 @@ - # AGENTS.md ## Projektoversigt diff --git a/translations/da/CODE_OF_CONDUCT.md b/translations/da/CODE_OF_CONDUCT.md index 80e3b6035..17aa3fd4c 100644 --- a/translations/da/CODE_OF_CONDUCT.md +++ b/translations/da/CODE_OF_CONDUCT.md @@ -1,12 +1,3 @@ - # Microsoft Open Source Adfærdskodeks Dette projekt har vedtaget [Microsoft Open Source Adfærdskodeks](https://opensource.microsoft.com/codeofconduct/). diff --git a/translations/da/CONTRIBUTING.md b/translations/da/CONTRIBUTING.md index 2d0ddc5af..2453d0fb7 100644 --- a/translations/da/CONTRIBUTING.md +++ b/translations/da/CONTRIBUTING.md @@ -1,12 +1,3 @@ - # Bidrag Dette projekt byder velkommen til bidrag og forslag. De fleste bidrag kræver, at du diff --git a/translations/da/README.md b/translations/da/README.md index 42dc373a5..811e4742f 100644 --- a/translations/da/README.md +++ b/translations/da/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/) -### 🌐 Multisprog Support +### 🌐 Multi-sprog support -#### Understøttet via GitHub Action (Automatiseret & Altid Opdateret) +#### Understøttet via GitHub Action (Automatisk & altid opdateret) -[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](./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)](../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) +[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](./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)](../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) > **Foretrækker du at klone lokalt?** -> Dette arkiv inkluderer over 50 sprogoversættelser, hvilket væsentligt øger downloadstørrelsen. For at klone uden oversættelser, brug sparse checkout: +> Dette repo indeholder 50+ sprogoversættelser, hvilket væsentligt øger downloadstørrelsen. For at klone uden oversættelser, brug 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' > ``` -> Dette giver dig alt, hvad du behøver for at fuldføre kurset med en meget hurtigere download. +> Dette giver dig alt hvad du behøver for at gennemføre kurset med en meget hurtigere download. #### Deltag i vores fællesskab [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -Vi har en igangværende Discord lær-serie med AI, lær mere og deltag hos [Learn with AI Series](https://aka.ms/learnwithai/discord) fra 18. - 30. september 2025. Du får tips og tricks til brug af GitHub Copilot til Data Science. +Vi har en Discord-serie "lær med AI" i gang, lær mere og deltag hos [Learn with AI Series](https://aka.ms/learnwithai/discord) fra 18. - 30. september 2025. Du vil få tips og tricks til brugen af GitHub Copilot til data science. -![Learn with AI series](../../../../translated_images/da/3.9b58fd8d6c373c20.webp) +![Learn with AI series](../../translated_images/da/3.9b58fd8d6c373c20.webp) -# Maskinlæring for Begyndere - En Læreplan +# Machine Learning for Beginners - En læseplan -> 🌍 Rejs rundt i verden, mens vi udforsker Maskinlæring gennem verdens kulturer 🌍 +> 🌍 Rejs rundt i verden, mens vi udforsker maskinlæring gennem verdens kulturer 🌍 -Cloud Advocates hos Microsoft er glade for at tilbyde en 12-ugers, 26-lektioners læreplan om **Maskinlæring**. I denne læreplan vil du lære om det, der nogle gange kaldes **klassisk maskinlæring**, primært ved brug af Scikit-learn som bibliotek og uden at dække dyb læring, som behandles i vores [AI for Beginners' læreplan](https://aka.ms/ai4beginners). Kombiner disse lektioner med vores ['Data Science for Beginners' læreplan](https://aka.ms/ds4beginners) også! +Cloud Advocates hos Microsoft tilbyder en 12-ugers, 26-lektioners læseplan om **Maskinlæring**. I denne læseplan lærer du om det, der med et andet ord kaldes **klassisk maskinlæring**, primært ved brug af Scikit-learn som bibliotek og uden dyb læring, som dækkes i vores [AI for Beginners-læseplan](https://aka.ms/ai4beginners). Kombiner disse lektioner med vores ['Data Science for Beginners'-læseplan](https://aka.ms/ds4beginners) også! -Rejs med os rundt i verden, mens vi anvender disse klassiske teknikker på data fra mange verdensdele. Hver lektion indeholder quizzer før og efter lektionen, skriftlige instruktioner til at gennemføre lektionen, en løsning, en opgave og mere. Vores projektbaserede pædagogik giver dig mulighed for at lære ved at bygge, en gennemprøvet måde at få nye færdigheder til at "sidde fast". +Rejs med os rundt i verden, mens vi anvender disse klassiske teknikker på data fra mange områder. Hver lektion indeholder quizzer før og efter lektionen, skriftlige instruktioner til at fuldføre lektionen, en løsning, en opgave og mere. Vores projektbaserede metode giver dig mulighed for at lære mens du bygger, en bevist måde at få nye færdigheder til at 'sætte sig'. -**✍️ Hjertelig tak til vores forfattere** Jen Looper, Stephen Howell, Francesca Lazzeri, Tomomi Imura, Cassie Breviu, Dmitry Soshnikov, Chris Noring, Anirban Mukherjee, Ornella Altunyan, Ruth Yakubu og Amy Boyd +**✍️ Hjertevarme tak til vores forfattere** Jen Looper, Stephen Howell, Francesca Lazzeri, Tomomi Imura, Cassie Breviu, Dmitry Soshnikov, Chris Noring, Anirban Mukherjee, Ornella Altunyan, Ruth Yakubu og Amy Boyd **🎨 Tak også til vores illustratorer** Tomomi Imura, Dasani Madipalli og Jen Looper -**🙏 Særlige tak 🙏 til vores Microsoft Student Ambassador-forfattere, anmeldere og indholdsbidragsydere**, især Rishit Dagli, Muhammad Sakib Khan Inan, Rohan Raj, Alexandru Petrescu, Abhishek Jaiswal, Nawrin Tabassum, Ioan Samuila og Snigdha Agarwal +**🙏 Særlig tak 🙏 til vores Microsoft Student Ambassador-forfattere, anmeldere og indholdsbidragydere**, især Rishit Dagli, Muhammad Sakib Khan Inan, Rohan Raj, Alexandru Petrescu, Abhishek Jaiswal, Nawrin Tabassum, Ioan Samuila og Snigdha Agarwal **🤩 Ekstra tak til Microsoft Student Ambassadors Eric Wanjau, Jasleen Sondhi og Vidushi Gupta for vores R-lektioner!** -# Kom godt i gang +# Kom i gang Følg disse trin: -1. **Fork repository**: Klik på "Fork" knappen øverst til højre på denne side. -2. **Klon repository**: `git clone https://github.com/microsoft/ML-For-Beginners.git` +1. **Fork Repoet**: Klik på "Fork" knappen øverst til højre på denne side. +2. **Klon Repoet**: `git clone https://github.com/microsoft/ML-For-Beginners.git` > [find alle yderligere ressourcer til dette kursus i vores Microsoft Learn-samling](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) -> 🔧 **Brug for hjælp?** Tjek vores [Fejlfinding guide](TROUBLESHOOTING.md) for løsninger på almindelige problemer med installation, opsætning og afvikling af lektioner. +> 🔧 **Brug for hjælp?** Se vores [Fejlfinding-guide](TROUBLESHOOTING.md) for løsninger på almindelige problemer med installation, opsætning og kørsel af lektioner. -**[Studerende](https://aka.ms/student-page)**, for at bruge denne læreplan, forke hele repoet til din egen GitHub-konto og gennemfør øvelserne alene eller i en gruppe: +**[Studerende](https://aka.ms/student-page)**, for at bruge denne læseplan, fork det hele repo til din egen GitHub-konto og gennemfør øvelserne på egen hånd eller i gruppe: -- Start med en quiz før forelæsningen. -- Læs forelæsningen og gennemfør aktiviteterne, stop op og reflekter ved hver videnscheck. -- Prøv at skabe projekterne ved at forstå lektionerne fremfor blot at køre løsningskoden; dog er denne kode tilgængelig i `/solution`-mapperne i hver projektorienteret lektion. -- Tag quizzen efter forelæsningen. -- Gennemfør udfordringen. -- Gennemfør opgaven. -- Efter at have fuldført en lektion gruppe, besøg [Diskussionsforum](https://github.com/microsoft/ML-For-Beginners/discussions) og "lær højt" ved at udfylde den passende PAT-rubrik. En 'PAT' er et fremskridtsvurderingsværktøj, som er en rubrik du udfylder for at fremme din læring. Du kan også reagere på andre PAT’er, så vi kan lære sammen. +- Start med en quiz før lektionen. +- Læs lektionen og fuldfør aktiviteterne, pause og reflektere ved hver videnstest. +- Forsøg at skabe projekterne ved at forstå lektionerne i stedet for blot at køre løsningskoden; denne kode er dog tilgængelig i `/solution` mapperne i hver projektorienteret lektion. +- Tag quizzen efter lektionen. +- Fuldfør udfordringen. +- Fuldfør opgaven. +- Efter at have gennemført en lektiongruppe, besøg [Diskussionspanelet](https://github.com/microsoft/ML-For-Beginners/discussions) og "lær højt" ved at udfylde den relevante PAT-rubrik. En 'PAT' er et Progress Assessment Tool, som er en rubrik du udfylder for at fremme din læring. Du kan også reagere på andre PATs, så vi kan lære sammen. -> For yderligere studier anbefaler vi at følge disse [Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/k7o7tg1gp306q4?WT.mc_id=academic-77952-leestott) moduler og læringsstier. +> Til videre studier anbefaler vi at følge disse [Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/k7o7tg1gp306q4?WT.mc_id=academic-77952-leestott) moduler og læringsforløb. -**Lærere**, vi har [inkluderet nogle forslag](for-teachers.md) til, hvordan man bruger denne læreplan. +**Undervisere**, vi har [inkluderet nogle forslag](for-teachers.md) til, hvordan denne læseplan kan anvendes. --- ## Video-gennemgange -Nogle af lektionerne findes som korte videoer. Du kan finde dem alle integreret i lektionerne eller på [ML for Beginners playliste på Microsoft Developers YouTube kanal](https://aka.ms/ml-beginners-videos) ved at klikke på billedet nedenfor. +Nogle af lektionerne findes som korte videoer. Du kan finde dem alle integreret i lektionerne eller på [ML for Beginners-afspilningslisten på Microsoft Developer YouTube-kanalen](https://aka.ms/ml-beginners-videos) ved at klikke på billedet nedenfor. -[![ML for beginners banner](../../../../translated_images/da/ml-for-beginners-video-banner.63f694a100034bc6.webp)](https://aka.ms/ml-beginners-videos) +[![ML for beginners banner](../../translated_images/da/ml-for-beginners-video-banner.63f694a100034bc6.webp)](https://aka.ms/ml-beginners-videos) --- @@ -100,79 +91,79 @@ Nogle af lektionerne findes som korte videoer. Du kan finde dem alle integreret **Gif af** [Mohit Jaisal](https://linkedin.com/in/mohitjaisal) -> 🎥 Klik på billedet ovenfor for en video om projektet og folkene, der skabte det! +> 🎥 Klik på billedet ovenfor for en video om projektet og folkene bag! --- ## Pædagogik -Vi har valgt to pædagogiske principper under opbygningen af denne læreplan: at sikre, at den er praktisk **projektbaseret** og at den indeholder **hyppige quizzer**. Derudover har denne læreplan et fælles **tema** for at skabe sammenhæng. +Vi har valgt to pædagogiske principper under udviklingen af denne læseplan: sikring af at den er praktisk **projektbaseret** og at den inkluderer **hyppige quizzer**. Derudover har læseplanen et fælles **tema** for at give den sammenhæng. -Ved at sikre at indholdet stemmer overens med projekterne, gøres processen mere engagerende for eleverne, og fastholdelse af begreber vil blive forstærket. Derudover sætter en quiz med lav indsats før en lektion elevens intention mod at lære et emne, mens en anden quiz efter lektionen sikrer øget fastholdelse. Denne læreplan er designet til at være fleksibel og sjov og kan tages helt eller delvist. Projekterne starter små og bliver mere komplekse i slutningen af det 12-ugers forløb. Denne læreplan inkluderer også et efterord om virkelige anvendelser af ML, som kan bruges som ekstra kredit eller som grundlag for diskussion. +Ved at sikre, at indholdet stemmer overens med projekterne, gøres processen mere engagerende for eleverne, og fastholdelsen af koncepter styrkes. En quiz med lav indsats før en klasse sætter elevens intention om at lære et emne, mens en anden quiz efter klassen sikrer yderligere fastholdelse. Denne læseplan er designet til at være fleksibel og sjov og kan tages helt eller delvist. Projekterne starter småt og bliver mere komplekse mod slutningen af 12-ugers perioden. Denne læseplan inkluderer også et efterskrift om maskinlæringens anvendelser i den virkelige verden, som kan bruges som ekstrakredit eller som grundlag for diskussion. -> Find vores [Adfærdskodeks](CODE_OF_CONDUCT.md), [Bidrag](CONTRIBUTING.md), [Oversættelse](TRANSLATIONS.md), og [Fejlfinding](TROUBLESHOOTING.md) retningslinjer. Vi byder dit konstruktive feedback velkommen! +> Find vores [Adfærdsregler](CODE_OF_CONDUCT.md), [Bidrag](CONTRIBUTING.md), [Oversættelse](TRANSLATIONS.md) og [Fejlfinding](TROUBLESHOOTING.md) retningslinjer. Vi værdsætter din konstruktive feedback! -## Hver lektion inkluderer +## Hver lektion indeholder -- valgfri sketchnote +- valgfrit sketchnote - valgfri supplerende video - video-gennemgang (kun nogle lektioner) -- [varme-op quiz før forelæsningen](https://ff-quizzes.netlify.app/en/ml/) +- [warmup-quiz før lektionen](https://ff-quizzes.netlify.app/en/ml/) - skriftlig lektion -- for projektbaserede lektioner, trin-for-trin vejledninger til hvordan man bygger projektet +- for projektbaserede lektioner: trin-for-trin vejledning til at bygge projektet - videnscheck - en udfordring - supplerende læsning - opgave -- [quiz efter forelæsningen](https://ff-quizzes.netlify.app/en/ml/) - -> **Et notat om sprog**: Disse lektioner er primært skrevet i Python, men mange er også tilgængelige i R. For at gennemføre en R-lektion, gå til `/solution` mappen og find R-lektionerne. De inkluderer en .rmd-udvidelse, som repræsenterer en **R Markdown** fil, der kan defineres som en indlejring af `kodeblokke` (af R eller andre sprog) og en `YAML header` (der guider, hvordan output som PDF skal formateres) i et `Markdown dokument`. Som sådan fungerer det som en eksemplarisk forfatterramme for datalogi, da det giver mulighed for at kombinere din kode, dens output og dine tanker ved at skrive dem ned i Markdown. Desuden kan R Markdown-dokumenter genereres til outputformater såsom PDF, HTML eller Word. -> **En note om quizzer**: Alle quizzer findes i [Quiz App-mappen](../../quiz-app), med i alt 52 quizzer med tre spørgsmål hver. De er linket fra lektionerne, men quiz-appen kan køres lokalt; følg vejledningen i `quiz-app`-mappen for at hoste lokalt eller deploye til Azure. - -| Lektion Nummer | Emne | Lektionens Kategori | Læringsmål | Linket Lektion | Forfatter | -| :------------: | :----------------------------------------------------------: | :-----------------------------------------------------: | ----------------------------------------------------------------------------------------------------------------------------- | :-------------------------------------------------------------------------------------------------------------------------------------: | :----------------------------------------------------: | -| 01 | Introduktion til maskinlæring | [Introduktion](1-Introduction/README.md) | Lær de grundlæggende begreber bag maskinlæring | [Lektion](1-Introduction/1-intro-to-ML/README.md) | Muhammad | -| 02 | Maskinlæringens historie | [Introduktion](1-Introduction/README.md) | Lær historien bag dette felt | [Lektion](1-Introduction/2-history-of-ML/README.md) | Jen og Amy | -| 03 | Retfærdighed og maskinlæring | [Introduktion](1-Introduction/README.md) | Hvilke vigtige filosofiske spørgsmål omkring retfærdighed bør elever overveje, når de bygger og anvender ML-modeller? | [Lektion](1-Introduction/3-fairness/README.md) | Tomomi | -| 04 | Teknikker til maskinlæring | [Introduktion](1-Introduction/README.md) | Hvilke teknikker bruger ML-forskere til at bygge ML-modeller? | [Lektion](1-Introduction/4-techniques-of-ML/README.md) | Chris og Jen | -| 05 | Introduktion til regression | [Regression](2-Regression/README.md) | Kom i gang med Python og Scikit-learn til regressionsmodeller | [Python](2-Regression/1-Tools/README.md) • [R](../../2-Regression/1-Tools/solution/R/lesson_1.html) | Jen • Eric Wanjau | -| 06 | Nordamerikanske græskarpriser 🎃 | [Regression](2-Regression/README.md) | Visualiser og rens data som forberedelse til ML | [Python](2-Regression/2-Data/README.md) • [R](../../2-Regression/2-Data/solution/R/lesson_2.html) | Jen • Eric Wanjau | -| 07 | Nordamerikanske græskarpriser 🎃 | [Regression](2-Regression/README.md) | Byg lineære og polynomielle regressionsmodeller | [Python](2-Regression/3-Linear/README.md) • [R](../../2-Regression/3-Linear/solution/R/lesson_3.html) | Jen og Dmitry • Eric Wanjau | -| 08 | Nordamerikanske græskarpriser 🎃 | [Regression](2-Regression/README.md) | Byg en logistisk regressionsmodel | [Python](2-Regression/4-Logistic/README.md) • [R](../../2-Regression/4-Logistic/solution/R/lesson_4.html) | Jen • Eric Wanjau | -| 09 | En Web App 🔌 | [Web App](3-Web-App/README.md) | Byg en webapp til at bruge din trænede model | [Python](3-Web-App/1-Web-App/README.md) | Jen | -| 10 | Introduktion til klassifikation | [Classification](4-Classification/README.md) | Rens, forbered og visualiser dine data; introduktion til klassifikation | [Python](4-Classification/1-Introduction/README.md) • [R](../../4-Classification/1-Introduction/solution/R/lesson_10.html) | Jen og Cassie • Eric Wanjau | -| 11 | Lækre asiatiske og indiske køkkener 🍜 | [Classification](4-Classification/README.md) | Introduktion til klassifikatorer | [Python](4-Classification/2-Classifiers-1/README.md) • [R](../../4-Classification/2-Classifiers-1/solution/R/lesson_11.html) | Jen og Cassie • Eric Wanjau | -| 12 | Lækre asiatiske og indiske køkkener 🍜 | [Classification](4-Classification/README.md) | Flere klassifikatorer | [Python](4-Classification/3-Classifiers-2/README.md) • [R](../../4-Classification/3-Classifiers-2/solution/R/lesson_12.html) | Jen og Cassie • Eric Wanjau | -| 13 | Lækre asiatiske og indiske køkkener 🍜 | [Classification](4-Classification/README.md) | Byg en anbefalings-webapp ved hjælp af din model | [Python](4-Classification/4-Applied/README.md) | Jen | -| 14 | Introduktion til klyngedannelse | [Clustering](5-Clustering/README.md) | Rens, forbered og visualiser dine data; introduktion til klyngedannelse | [Python](5-Clustering/1-Visualize/README.md) • [R](../../5-Clustering/1-Visualize/solution/R/lesson_14.html) | Jen • Eric Wanjau | -| 15 | Udforskning af nigerianske musiksmag 🎧 | [Clustering](5-Clustering/README.md) | Udforsk K-Means klyngemetoden | [Python](5-Clustering/2-K-Means/README.md) • [R](../../5-Clustering/2-K-Means/solution/R/lesson_15.html) | Jen • Eric Wanjau | -| 16 | Introduktion til naturlig sprogbehandling ☕️ | [Natural language processing](6-NLP/README.md) | Lær det grundlæggende om NLP ved at bygge en simpel bot | [Python](6-NLP/1-Introduction-to-NLP/README.md) | Stephen | -| 17 | Almindelige NLP-opgaver ☕️ | [Natural language processing](6-NLP/README.md) | Forstå almindelige opgaver, som kræves ved håndtering af sprogstrukturer | [Python](6-NLP/2-Tasks/README.md) | Stephen | -| 18 | Oversættelse og sentimentanalyse ♥️ | [Natural language processing](6-NLP/README.md) | Oversættelse og sentimentanalyse med Jane Austen | [Python](6-NLP/3-Translation-Sentiment/README.md) | Stephen | -| 19 | Romantiske hoteller i Europa ♥️ | [Natural language processing](6-NLP/README.md) | Sentimentanalyse med hotelanmeldelser 1 | [Python](6-NLP/4-Hotel-Reviews-1/README.md) | Stephen | -| 20 | Romantiske hoteller i Europa ♥️ | [Natural language processing](6-NLP/README.md) | Sentimentanalyse med hotelanmeldelser 2 | [Python](6-NLP/5-Hotel-Reviews-2/README.md) | Stephen | -| 21 | Introduktion til tidsseriefremskrivning | [Time series](7-TimeSeries/README.md) | Introduktion til tidsseriefremskrivning | [Python](7-TimeSeries/1-Introduction/README.md) | Francesca | -| 22 | ⚡️ Verdens strømforbrug ⚡️ - tidsseriefremskrivning med ARIMA | [Time series](7-TimeSeries/README.md) | Tidsseriefremskrivning med ARIMA | [Python](7-TimeSeries/2-ARIMA/README.md) | Francesca | -| 23 | ⚡️ Verdens strømforbrug ⚡️ - tidsseriefremskrivning med SVR | [Time series](7-TimeSeries/README.md) | Tidsseriefremskrivning med Support Vector Regressor | [Python](7-TimeSeries/3-SVR/README.md) | Anirban | -| 24 | Introduktion til forstærkningslæring | [Reinforcement learning](8-Reinforcement/README.md) | Introduktion til forstærkningslæring med Q-Learning | [Python](8-Reinforcement/1-QLearning/README.md) | Dmitry | -| 25 | Hjælp Peter med at undgå ulven! 🐺 | [Reinforcement learning](8-Reinforcement/README.md) | Forstærkningslæring i Gym | [Python](8-Reinforcement/2-Gym/README.md) | Dmitry | -| Efterskrift | Reelle ML-scenarier og -anvendelser | [ML in the Wild](9-Real-World/README.md) | Interessante og oplysende virkelige anvendelser af klassisk ML | [Lektion](9-Real-World/1-Applications/README.md) | Team | -| Efterskrift | Fejlfinding af ML-modeller med RAI dashboard | [ML in the Wild](9-Real-World/README.md) | Fejlfinding af ML-modeller ved hjælp af Responsible AI-dashboard komponenter | [Lektion](9-Real-World/2-Debugging-ML-Models/README.md) | Ruth Yakubu | - -> [find alle yderligere ressourcer til dette kursus i vores Microsoft Learn-samling](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) +- [quiz efter lektionen](https://ff-quizzes.netlify.app/en/ml/) + +> **En note om sprog**: Disse lektioner er primært skrevet i Python, men mange findes også i R. For at gennemføre en R-lektion, gå til `/solution` mappen og se efter R-lektioner. De har en .rmd extension, som repræsenterer en **R Markdown**-fil, der enkelt kan defineres som en sammenstilling af `kodeblokke` (fra R eller andre sprog) og en `YAML-header` (som styrer formateringen af output som PDF) i et `Markdown-dokument`. Dermed fungerer det som en fremragende forfatter-ramme for data science, da det lader dig kombinere din kode, dens output og dine tanker ved at skrive dem ned i Markdown. Desuden kan R Markdown-dokumenter gengives til outputformater som PDF, HTML eller Word. +> **En note om quizzer**: Alle quizzer findes i [Quiz App mappen](../../quiz-app), i alt 52 quizzer med tre spørgsmål hver. De er linket fra lektionerne, men quiz-app'en kan køres lokalt; følg instruktionerne i `quiz-app` mappen for at hoste lokalt eller deploye til Azure. + +| Lektion Nummer | Emne | Lektion Gruppe | Læringsmål | Linket Lektion | Forfatter | +| :------------: | :------------------------------------------------------------: | :------------------------------------------------: | ----------------------------------------------------------------------------------------------------------------------------- | :---------------------------------------------------------------------------------------------------------------------------------------: | :----------------------------------------------------: | +| 01 | Introduktion til maskinlæring | [Introduktion](1-Introduction/README.md) | Lær de grundlæggende begreber bag maskinlæring | [Lektion](1-Introduction/1-intro-to-ML/README.md) | Muhammad | +| 02 | Historien om maskinlæring | [Introduktion](1-Introduction/README.md) | Lær historien bag dette felt | [Lektion](1-Introduction/2-history-of-ML/README.md) | Jen og Amy | +| 03 | Retfærdighed og maskinlæring | [Introduktion](1-Introduction/README.md) | Hvad er de vigtige filosofiske spørgsmål omkring retfærdighed, som elever bør overveje, når de bygger og anvender ML-modeller? | [Lektion](1-Introduction/3-fairness/README.md) | Tomomi | +| 04 | Teknikker til maskinlæring | [Introduktion](1-Introduction/README.md) | Hvilke teknikker bruger ML-forskere til at bygge ML-modeller? | [Lektion](1-Introduction/4-techniques-of-ML/README.md) | Chris og Jen | +| 05 | Introduktion til regression | [Regression](2-Regression/README.md) | Kom i gang med Python og Scikit-learn til regressionsmodeller | [Python](2-Regression/1-Tools/README.md) • [R](../../2-Regression/1-Tools/solution/R/lesson_1.html) | Jen • Eric Wanjau | +| 06 | Nordamerikanske græskarpriser 🎃 | [Regression](2-Regression/README.md) | Visualisere og rense data som forberedelse til ML | [Python](2-Regression/2-Data/README.md) • [R](../../2-Regression/2-Data/solution/R/lesson_2.html) | Jen • Eric Wanjau | +| 07 | Nordamerikanske græskarpriser 🎃 | [Regression](2-Regression/README.md) | Byg lineære og polynomiske regressionsmodeller | [Python](2-Regression/3-Linear/README.md) • [R](../../2-Regression/3-Linear/solution/R/lesson_3.html) | Jen og Dmitry • Eric Wanjau | +| 08 | Nordamerikanske græskarpriser 🎃 | [Regression](2-Regression/README.md) | Byg en logistisk regressionsmodel | [Python](2-Regression/4-Logistic/README.md) • [R](../../2-Regression/4-Logistic/solution/R/lesson_4.html) | Jen • Eric Wanjau | +| 09 | En webapp 🔌 | [Web App](3-Web-App/README.md) | Byg en webapp til at bruge din trænede model | [Python](3-Web-App/1-Web-App/README.md) | Jen | +| 10 | Introduktion til klassifikation | [Classification](4-Classification/README.md) | Rens, forbered og visualiser dine data; introduktion til klassifikation | [Python](4-Classification/1-Introduction/README.md) • [R](../../4-Classification/1-Introduction/solution/R/lesson_10.html) | Jen og Cassie • Eric Wanjau | +| 11 | Lækre asiatiske og indiske retter 🍜 | [Classification](4-Classification/README.md) | Introduktion til klassifikatorer | [Python](4-Classification/2-Classifiers-1/README.md) • [R](../../4-Classification/2-Classifiers-1/solution/R/lesson_11.html) | Jen og Cassie • Eric Wanjau | +| 12 | Lækre asiatiske og indiske retter 🍜 | [Classification](4-Classification/README.md) | Flere klassifikatorer | [Python](4-Classification/3-Classifiers-2/README.md) • [R](../../4-Classification/3-Classifiers-2/solution/R/lesson_12.html) | Jen og Cassie • Eric Wanjau | +| 13 | Lækre asiatiske og indiske retter 🍜 | [Classification](4-Classification/README.md) | Byg en anbefalings-webapp ved hjælp af din model | [Python](4-Classification/4-Applied/README.md) | Jen | +| 14 | Introduktion til clustering | [Clustering](5-Clustering/README.md) | Rens, forbered og visualiser dine data; introduktion til clustering | [Python](5-Clustering/1-Visualize/README.md) • [R](../../5-Clustering/1-Visualize/solution/R/lesson_14.html) | Jen • Eric Wanjau | +| 15 | Udforskning af nigerianske musiksmag 🎧 | [Clustering](5-Clustering/README.md) | Udforsk K-Means clustering metoden | [Python](5-Clustering/2-K-Means/README.md) • [R](../../5-Clustering/2-K-Means/solution/R/lesson_15.html) | Jen • Eric Wanjau | +| 16 | Introduktion til naturlig sprogbehandling ☕️ | [Natural language processing](6-NLP/README.md) | Lær det grundlæggende om NLP ved at bygge en simpel bot | [Python](6-NLP/1-Introduction-to-NLP/README.md) | Stephen | +| 17 | Almindelige NLP opgaver ☕️ | [Natural language processing](6-NLP/README.md) | Fordyb din NLP-viden ved at forstå almindelige opgaver, der kræves ved håndtering af sproglige strukturer | [Python](6-NLP/2-Tasks/README.md) | Stephen | +| 18 | Oversættelse og sentimentanalyse ♥️ | [Natural language processing](6-NLP/README.md) | Oversættelse og sentimentanalyse med Jane Austen | [Python](6-NLP/3-Translation-Sentiment/README.md) | Stephen | +| 19 | Romantiske hoteller i Europa ♥️ | [Natural language processing](6-NLP/README.md) | Sentimentanalyse med hotelanmeldelser 1 | [Python](6-NLP/4-Hotel-Reviews-1/README.md) | Stephen | +| 20 | Romantiske hoteller i Europa ♥️ | [Natural language processing](6-NLP/README.md) | Sentimentanalyse med hotelanmeldelser 2 | [Python](6-NLP/5-Hotel-Reviews-2/README.md) | Stephen | +| 21 | Introduktion til tidsserieprognose | [Time series](7-TimeSeries/README.md) | Introduktion til tidsserieprognose | [Python](7-TimeSeries/1-Introduction/README.md) | Francesca | +| 22 | ⚡️ Verdens strømforbrug ⚡️ - tidsserieprognose med ARIMA | [Time series](7-TimeSeries/README.md) | Tidsserieprognose med ARIMA | [Python](7-TimeSeries/2-ARIMA/README.md) | Francesca | +| 23 | ⚡️ Verdens strømforbrug ⚡️ - tidsserieprognose med SVR | [Time series](7-TimeSeries/README.md) | Tidsserieprognose med Support Vector Regressor | [Python](7-TimeSeries/3-SVR/README.md) | Anirban | +| 24 | Introduktion til reinforcement learning | [Reinforcement learning](8-Reinforcement/README.md) | Introduktion til reinforcement learning med Q-Learning | [Python](8-Reinforcement/1-QLearning/README.md) | Dmitry | +| 25 | Hjælp Peter med at undgå ulven! 🐺 | [Reinforcement learning](8-Reinforcement/README.md) | Reinforcement learning Gym | [Python](8-Reinforcement/2-Gym/README.md) | Dmitry | +| Efterskrift | Virkelige ML scenarier og anvendelser | [ML in the Wild](9-Real-World/README.md) | Interessante og afslørende virkelige anvendelser af klassisk ML | [Lektion](9-Real-World/1-Applications/README.md) | Team | +| Efterskrift | Modelafhjælpning i ML ved brug af RAI dashboard | [ML in the Wild](9-Real-World/README.md) | Modelafhjælpning i maskinlæring ved brug af Responsible AI dashboard komponenter | [Lektion](9-Real-World/2-Debugging-ML-Models/README.md) | Ruth Yakubu | + +> [find alle yderligere ressourcer til dette kursus i vores Microsoft Learn samling](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) ## Offline adgang -Du kan køre denne dokumentation offline ved at bruge [Docsify](https://docsify.js.org/#/). Fork dette repo, [installer Docsify](https://docsify.js.org/#/quickstart) på din lokale maskine, og derefter i root-mappen af dette repo, skriv `docsify serve`. Hjemmesiden vil blive serveret på port 3000 på din localhost: `localhost:3000`. +Du kan køre denne dokumentation offline ved hjælp af [Docsify](https://docsify.js.org/#/). Fork dette repo, [installer Docsify](https://docsify.js.org/#/quickstart) på din lokale maskine, og skriv derefter i rodmappen af dette repo `docsify serve`. Websitet vil blive servet på port 3000 på din localhost: `localhost:3000`. ## PDF'er -Find et pdf-udgave af pensum med links [her](https://microsoft.github.io/ML-For-Beginners/pdf/readme.pdf). +Find en pdf af pensum med links [her](https://microsoft.github.io/ML-For-Beginners/pdf/readme.pdf). -## 🎒 Andre kurser +## 🎒 Andre kurser -Vores team producerer andre kurser! Se her: +Vores team producerer andre kurser! Tjek dem ud: ### LangChain @@ -189,44 +180,44 @@ Vores team producerer andre kurser! Se her: --- -### Generativ AI-serie -[![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 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Begyndere](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 Begyndere](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 Begyndere](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) +[![Cybersikkerhed for Begyndere](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) +[![Webudvikling for Begyndere](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 Begyndere](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-udvikling for Begyndere](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) --- ### Copilot Serie -[![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 AI Parprogrammering](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 Eventyr](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) -## Få Hjælp +## Få hjælp -Hvis du sidder fast eller har spørgsmål om at bygge AI-apps. Deltag i samtaler med andre lærende og erfarne udviklere om MCP. Det er et støttende fællesskab, hvor spørgsmål er velkomne, og viden deles frit. +Hvis du sidder fast eller har spørgsmål om at bygge AI-apps. Deltag med andre lærende og erfarne udviklere i diskussioner om MCP. Det er et støttende fællesskab, hvor spørgsmål er velkomne, og viden deles frit. [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -Hvis du har produktfeedback eller fejl under udvikling, besøg: +Hvis du har feedback på produktet eller fejl under udviklingen, besøg: [![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) --- -**Ansvarsfraskrivelse**: -Dette dokument er blevet oversat ved hjælp af AI-oversættelsestjenesten [Co-op Translator](https://github.com/Azure/co-op-translator). Selvom vi bestræber os på nøjagtighed, skal du være opmærksom på, at automatiserede oversættelser kan indeholde fejl eller unøjagtigheder. Det oprindelige dokument på dets oprindelige sprog bør anses som den autoritative kilde. For kritisk information anbefales professionel menneskelig oversættelse. Vi kan ikke drages til ansvar for misforståelser eller fejltolkninger, der måtte opstå ved brug af denne oversættelse. +**Ansvarsfraskrivelse**: +Dette dokument er oversat ved hjælp af AI-oversættelsestjenesten [Co-op Translator](https://github.com/Azure/co-op-translator). Selvom vi bestræber os på nøjagtighed, bedes du være opmærksom på, at automatiserede oversættelser kan indeholde fejl eller unøjagtigheder. Det oprindelige dokument på dets modersmål bør betragtes som den autoritative kilde. For kritisk information anbefales professionel menneskelig oversættelse. Vi påtager os intet ansvar for misforståelser eller fejltolkninger, der måtte opstå som følge af brugen af denne oversættelse. \ No newline at end of file diff --git a/translations/da/SECURITY.md b/translations/da/SECURITY.md index fb81310aa..218e317f9 100644 --- a/translations/da/SECURITY.md +++ b/translations/da/SECURITY.md @@ -1,12 +1,3 @@ - ## Sikkerhed Microsoft tager sikkerheden af vores softwareprodukter og -tjenester alvorligt, hvilket inkluderer alle kildekoderepositorier, der administreres gennem vores GitHub-organisationer, som inkluderer [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) og [vores GitHub-organisationer](https://opensource.microsoft.com/). diff --git a/translations/da/SUPPORT.md b/translations/da/SUPPORT.md index c3583781f..9a5bd831c 100644 --- a/translations/da/SUPPORT.md +++ b/translations/da/SUPPORT.md @@ -1,12 +1,3 @@ - # Support ## Sådan indsender du problemer og får hjælp diff --git a/translations/da/TROUBLESHOOTING.md b/translations/da/TROUBLESHOOTING.md index 64656d85a..8bbc74d15 100644 --- a/translations/da/TROUBLESHOOTING.md +++ b/translations/da/TROUBLESHOOTING.md @@ -1,12 +1,3 @@ - # Fejlfindingsguide Denne guide hjælper dig med at løse almindelige problemer, når du arbejder med Machine Learning for Beginners-kurset. Hvis du ikke finder en løsning her, kan du tjekke vores [Discord-diskussioner](https://aka.ms/foundry/discord) eller [oprette en sag](https://github.com/microsoft/ML-For-Beginners/issues). diff --git a/translations/da/docs/_sidebar.md b/translations/da/docs/_sidebar.md index eb2d10f96..ac467218e 100644 --- a/translations/da/docs/_sidebar.md +++ b/translations/da/docs/_sidebar.md @@ -1,12 +1,3 @@ - - Introduktion - [Introduktion til Maskinlæring](../1-Introduction/1-intro-to-ML/README.md) - [Historien om Maskinlæring](../1-Introduction/2-history-of-ML/README.md) diff --git a/translations/da/for-teachers.md b/translations/da/for-teachers.md index c5aff3690..d9c729090 100644 --- a/translations/da/for-teachers.md +++ b/translations/da/for-teachers.md @@ -1,12 +1,3 @@ - ## For undervisere Vil du gerne bruge dette pensum i din undervisning? Du er meget velkommen! diff --git a/translations/da/quiz-app/README.md b/translations/da/quiz-app/README.md index b72b30dce..559b168c0 100644 --- a/translations/da/quiz-app/README.md +++ b/translations/da/quiz-app/README.md @@ -1,12 +1,3 @@ - # Quizzer Disse quizzer er før- og efterforelæsningsquizzer for ML-kurset på https://aka.ms/ml-beginners diff --git a/translations/da/sketchnotes/LICENSE.md b/translations/da/sketchnotes/LICENSE.md index 6e674064d..8fbd29094 100644 --- a/translations/da/sketchnotes/LICENSE.md +++ b/translations/da/sketchnotes/LICENSE.md @@ -1,12 +1,3 @@ - Rettigheder, så licenserer du den resulterende database under de samme betingelser som denne offentlige licens; c. du må ikke tilbyde eller pålægge yderligere eller forskellige vilkår eller betingelser for, eller anvende Effektive Teknologiske Foranstaltninger på, den licenserede database, der begrænser udøvelsen af de rettigheder, der er givet under denne offentlige licens; og diff --git a/translations/da/sketchnotes/README.md b/translations/da/sketchnotes/README.md index a3106b118..060e87056 100644 --- a/translations/da/sketchnotes/README.md +++ b/translations/da/sketchnotes/README.md @@ -1,12 +1,3 @@ - Alle sketchnotes fra pensum kan downloades her. 🖨 For udskrivning i høj opløsning er TIFF-versionerne tilgængelige på [dette repo](https://github.com/girliemac/a-picture-is-worth-a-1000-words/tree/main/ml/tiff). diff --git a/translations/fi/.co-op-translator.json b/translations/fi/.co-op-translator.json new file mode 100644 index 000000000..1880a7704 --- /dev/null +++ b/translations/fi/.co-op-translator.json @@ -0,0 +1,596 @@ +{ + "1-Introduction/1-intro-to-ML/README.md": { + "original_hash": "69389392fa6346e0dfa30f664b7b6fec", + "translation_date": "2025-09-05T00:31:44+00:00", + "source_file": "1-Introduction/1-intro-to-ML/README.md", + "language_code": "fi" + }, + "1-Introduction/1-intro-to-ML/assignment.md": { + "original_hash": "4c4698044bb8af52cfb6388a4ee0e53b", + 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"a88d5918c1b9da69a40d917a0840c497", + "translation_date": "2025-09-05T00:55:51+00:00", + "source_file": "sketchnotes/README.md", + "language_code": "fi" + } +} \ No newline at end of file diff --git a/translations/fi/1-Introduction/1-intro-to-ML/README.md b/translations/fi/1-Introduction/1-intro-to-ML/README.md index 1b910ee19..e6d01cffe 100644 --- a/translations/fi/1-Introduction/1-intro-to-ML/README.md +++ b/translations/fi/1-Introduction/1-intro-to-ML/README.md @@ -1,12 +1,3 @@ - # Johdatus koneoppimiseen ## [Ennakkokysely](https://ff-quizzes.netlify.app/en/ml/) diff --git a/translations/fi/1-Introduction/1-intro-to-ML/assignment.md b/translations/fi/1-Introduction/1-intro-to-ML/assignment.md index 25c6cef50..e41dcc725 100644 --- a/translations/fi/1-Introduction/1-intro-to-ML/assignment.md +++ b/translations/fi/1-Introduction/1-intro-to-ML/assignment.md @@ -1,12 +1,3 @@ - # Aloita ja pääse vauhtiin ## Ohjeet diff --git a/translations/fi/1-Introduction/2-history-of-ML/README.md b/translations/fi/1-Introduction/2-history-of-ML/README.md index f0e12b760..5bf37a900 100644 --- a/translations/fi/1-Introduction/2-history-of-ML/README.md +++ b/translations/fi/1-Introduction/2-history-of-ML/README.md @@ -1,12 +1,3 @@ - # Koneoppimisen historia ![Yhteenveto koneoppimisen historiasta sketchnotena](../../../../sketchnotes/ml-history.png) diff --git a/translations/fi/1-Introduction/2-history-of-ML/assignment.md b/translations/fi/1-Introduction/2-history-of-ML/assignment.md index fe17f6d14..28271fbb9 100644 --- a/translations/fi/1-Introduction/2-history-of-ML/assignment.md +++ b/translations/fi/1-Introduction/2-history-of-ML/assignment.md @@ -1,12 +1,3 @@ - # Luo aikajana ## Ohjeet diff --git a/translations/fi/1-Introduction/3-fairness/README.md b/translations/fi/1-Introduction/3-fairness/README.md index 993e881bb..a7a266d33 100644 --- a/translations/fi/1-Introduction/3-fairness/README.md +++ b/translations/fi/1-Introduction/3-fairness/README.md @@ -1,12 +1,3 @@ - # Rakentamassa koneoppimisratkaisuja vastuullisen tekoälyn avulla ![Yhteenveto vastuullisesta tekoälystä koneoppimisessa sketchnotessa](../../../../sketchnotes/ml-fairness.png) diff --git a/translations/fi/1-Introduction/3-fairness/assignment.md b/translations/fi/1-Introduction/3-fairness/assignment.md index fd30237d2..c5c37e6aa 100644 --- a/translations/fi/1-Introduction/3-fairness/assignment.md +++ b/translations/fi/1-Introduction/3-fairness/assignment.md @@ -1,12 +1,3 @@ - # Tutustu Responsible AI Toolboxiin ## Ohjeet diff --git a/translations/fi/1-Introduction/4-techniques-of-ML/README.md b/translations/fi/1-Introduction/4-techniques-of-ML/README.md index f3b867acd..7ac9b61f1 100644 --- a/translations/fi/1-Introduction/4-techniques-of-ML/README.md +++ b/translations/fi/1-Introduction/4-techniques-of-ML/README.md @@ -1,12 +1,3 @@ - # Koneoppimisen tekniikat Koneoppimismallien ja niiden käyttämän datan rakentaminen, käyttäminen ja ylläpito eroaa merkittävästi monista muista kehitysprosesseista. Tässä oppitunnissa selvitämme prosessin ja hahmotamme tärkeimmät tekniikat, jotka sinun tulee hallita. Opit: diff --git a/translations/fi/1-Introduction/4-techniques-of-ML/assignment.md b/translations/fi/1-Introduction/4-techniques-of-ML/assignment.md index fd4ab1dc4..c16cd29aa 100644 --- a/translations/fi/1-Introduction/4-techniques-of-ML/assignment.md +++ b/translations/fi/1-Introduction/4-techniques-of-ML/assignment.md @@ -1,12 +1,3 @@ - # Haastattele data-analyytikkoa ## Ohjeet diff --git a/translations/fi/1-Introduction/README.md b/translations/fi/1-Introduction/README.md index 24369c34f..451ff4a35 100644 --- a/translations/fi/1-Introduction/README.md +++ b/translations/fi/1-Introduction/README.md @@ -1,12 +1,3 @@ - # Johdatus koneoppimiseen Tässä opintokokonaisuuden osassa tutustut koneoppimisen peruskäsitteisiin, siihen mitä se on, sen historiaan sekä tekniikoihin, joita tutkijat käyttävät sen parissa työskennellessään. Tutkitaan yhdessä tätä uutta koneoppimisen maailmaa! diff --git a/translations/fi/2-Regression/1-Tools/README.md b/translations/fi/2-Regression/1-Tools/README.md index fbf1ca467..02624308c 100644 --- a/translations/fi/2-Regression/1-Tools/README.md +++ b/translations/fi/2-Regression/1-Tools/README.md @@ -1,12 +1,3 @@ - # Aloita Pythonin ja Scikit-learnin käyttö regressiomallien kanssa ![Yhteenveto regressioista luonnosmuistiinpanossa](../../../../sketchnotes/ml-regression.png) diff --git a/translations/fi/2-Regression/1-Tools/assignment.md b/translations/fi/2-Regression/1-Tools/assignment.md index 42e197203..355aac244 100644 --- a/translations/fi/2-Regression/1-Tools/assignment.md +++ b/translations/fi/2-Regression/1-Tools/assignment.md @@ -1,12 +1,3 @@ - # Regressio Scikit-learnilla ## Ohjeet diff --git a/translations/fi/2-Regression/1-Tools/solution/Julia/README.md b/translations/fi/2-Regression/1-Tools/solution/Julia/README.md index 14ecbdfd3..aacb66189 100644 --- a/translations/fi/2-Regression/1-Tools/solution/Julia/README.md +++ b/translations/fi/2-Regression/1-Tools/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/fi/2-Regression/2-Data/README.md b/translations/fi/2-Regression/2-Data/README.md index 75f9617a0..4c1405faf 100644 --- a/translations/fi/2-Regression/2-Data/README.md +++ b/translations/fi/2-Regression/2-Data/README.md @@ -1,12 +1,3 @@ - # Rakenna regressiomalli Scikit-learnilla: valmistele ja visualisoi data ![Datavisualisoinnin infografiikka](../../../../2-Regression/2-Data/images/data-visualization.png) diff --git a/translations/fi/2-Regression/2-Data/assignment.md b/translations/fi/2-Regression/2-Data/assignment.md index 49e9357bc..36df0e497 100644 --- a/translations/fi/2-Regression/2-Data/assignment.md +++ b/translations/fi/2-Regression/2-Data/assignment.md @@ -1,12 +1,3 @@ - # Tutkitaan visualisointeja On olemassa useita eri kirjastoja, jotka ovat saatavilla datan visualisointiin. Luo joitakin visualisointeja tämän oppitunnin kurpitsadataa käyttäen matplotlibin ja seabornin avulla näytekirjassa. Mitkä kirjastot ovat helpompia käyttää? diff --git a/translations/fi/2-Regression/2-Data/solution/Julia/README.md b/translations/fi/2-Regression/2-Data/solution/Julia/README.md index e360473e2..d9494a101 100644 --- a/translations/fi/2-Regression/2-Data/solution/Julia/README.md +++ b/translations/fi/2-Regression/2-Data/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/fi/2-Regression/3-Linear/README.md b/translations/fi/2-Regression/3-Linear/README.md index 8ca49ab79..3580a5097 100644 --- a/translations/fi/2-Regression/3-Linear/README.md +++ b/translations/fi/2-Regression/3-Linear/README.md @@ -1,12 +1,3 @@ - # Rakenna regressiomalli Scikit-learnilla: neljä tapaa regressioon ![Lineaarinen vs polynominen regressio infografiikka](../../../../2-Regression/3-Linear/images/linear-polynomial.png) @@ -114,11 +105,11 @@ Nyt kun ymmärrät lineaarisen regression taustalla olevan matematiikan, luodaan Edellisestä oppitunnista olet todennäköisesti nähnyt, että keskimääräinen hinta eri kuukausina näyttää tältä: -Keskimääräinen hinta kuukauden mukaan +Keskimääräinen hinta kuukauden mukaan Tämä viittaa siihen, että korrelaatiota saattaa olla, ja voimme yrittää kouluttaa lineaarisen regressiomallin ennustamaan suhdetta `Kuukausi` ja `Hinta` välillä tai `VuodenPäivä` ja `Hinta` välillä. Tässä on hajontakaavio, joka näyttää jälkimmäisen suhteen: -Hajontakaavio Hinta vs. Vuoden Päivä +Hajontakaavio Hinta vs. Vuoden Päivä Katsotaan, onko korrelaatiota käyttämällä `corr`-funktiota: @@ -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) ``` -Hajontakaavio Hinta vs. Vuoden Päivä +Hajontakaavio Hinta vs. Vuoden Päivä Tutkimuksemme viittaa siihen, että lajikkeella on suurempi vaikutus kokonaishintaan kuin varsinaisella myyntipäivällä. Voimme nähdä tämän pylväsdiagrammilla: @@ -145,7 +136,7 @@ Tutkimuksemme viittaa siihen, että lajikkeella on suurempi vaikutus kokonaishin new_pumpkins.groupby('Variety')['Price'].mean().plot(kind='bar') ``` -Pylväsdiagrammi hinta vs lajike +Pylväsdiagrammi hinta vs lajike Keskitytään hetkeksi vain yhteen kurpitsalajikkeeseen, 'pie type', ja katsotaan, mitä vaikutusta päivämäärällä on hintaan: @@ -153,7 +144,7 @@ Keskitytään hetkeksi vain yhteen kurpitsalajikkeeseen, 'pie type', ja katsotaa pie_pumpkins = new_pumpkins[new_pumpkins['Variety']=='PIE TYPE'] pie_pumpkins.plot.scatter('DayOfYear','Price') ``` -Hajontakaavio Hinta vs. Vuoden Päivä +Hajontakaavio Hinta vs. Vuoden Päivä Jos nyt laskemme korrelaation `Hinta` ja `VuodenPäivä` välillä käyttäen `corr`-funktiota, saamme jotain kuten `-0.27` - mikä tarkoittaa, että ennustavan mallin kouluttaminen on järkevää. @@ -227,7 +218,7 @@ plt.scatter(X_test,y_test) plt.plot(X_test,pred) ``` -Lineaarinen regressio +Lineaarinen regressio ## Polynominen regressio @@ -256,7 +247,7 @@ Käyttämällä `PolynomialFeatures(2)` tarkoittaa, että sisällytämme kaikki Pipelinea voidaan käyttää samalla tavalla kuin alkuperäistä `LinearRegression`-objektia, eli voimme `fit` pipelinea ja sitten käyttää `predict` saadaksemme ennustetulokset. Tässä on graafi, joka näyttää testidatan ja approksimaatiokäyrän: -Polynominen regressio +Polynominen regressio Polynomista regressiota käyttämällä voimme saada hieman pienemmän MSE:n ja korkeamman determinointikertoimen, mutta ei merkittävästi. Meidän täytyy ottaa huomioon muita ominaisuuksia! @@ -274,7 +265,7 @@ Ihanteellisessa maailmassa haluaisimme pystyä ennustamaan hinnat eri kurpitsala Tässä näet, miten keskimääräinen hinta riippuu lajikkeesta: -Keskimääräinen hinta lajikkeen mukaan +Keskimääräinen hinta lajikkeen mukaan Jotta voimme ottaa lajikkeen huomioon, meidän täytyy ensin muuntaa se numeeriseen muotoon eli **koodata** se. On olemassa useita tapoja tehdä tämä: diff --git a/translations/fi/2-Regression/3-Linear/assignment.md b/translations/fi/2-Regression/3-Linear/assignment.md index 1756aa559..e4c934bcf 100644 --- a/translations/fi/2-Regression/3-Linear/assignment.md +++ b/translations/fi/2-Regression/3-Linear/assignment.md @@ -1,12 +1,3 @@ - # Luo regressiomalli ## Ohjeet diff --git a/translations/fi/2-Regression/3-Linear/solution/Julia/README.md b/translations/fi/2-Regression/3-Linear/solution/Julia/README.md index 4258d61a2..d9494a101 100644 --- a/translations/fi/2-Regression/3-Linear/solution/Julia/README.md +++ b/translations/fi/2-Regression/3-Linear/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/fi/2-Regression/4-Logistic/README.md b/translations/fi/2-Regression/4-Logistic/README.md index ab7273387..853daab6f 100644 --- a/translations/fi/2-Regression/4-Logistic/README.md +++ b/translations/fi/2-Regression/4-Logistic/README.md @@ -1,12 +1,3 @@ - # Logistinen regressio kategorioiden ennustamiseen ![Logistinen vs. lineaarinen regressio -infografiikka](../../../../2-Regression/4-Logistic/images/linear-vs-logistic.png) diff --git a/translations/fi/2-Regression/4-Logistic/assignment.md b/translations/fi/2-Regression/4-Logistic/assignment.md index b03730778..a12f72d5b 100644 --- a/translations/fi/2-Regression/4-Logistic/assignment.md +++ b/translations/fi/2-Regression/4-Logistic/assignment.md @@ -1,12 +1,3 @@ - # Uudelleen yrittäminen regressiolla ## Ohjeet diff --git a/translations/fi/2-Regression/4-Logistic/solution/Julia/README.md b/translations/fi/2-Regression/4-Logistic/solution/Julia/README.md index 0d3c9945f..aacb66189 100644 --- a/translations/fi/2-Regression/4-Logistic/solution/Julia/README.md +++ b/translations/fi/2-Regression/4-Logistic/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/fi/2-Regression/README.md b/translations/fi/2-Regression/README.md index 7076f2da6..08d1fb26b 100644 --- a/translations/fi/2-Regression/README.md +++ b/translations/fi/2-Regression/README.md @@ -1,12 +1,3 @@ - # Regressiomallit koneoppimisessa ## Alueellinen aihe: Regressiomallit kurpitsan hinnoille Pohjois-Amerikassa 🎃 diff --git a/translations/fi/3-Web-App/1-Web-App/README.md b/translations/fi/3-Web-App/1-Web-App/README.md index bb09c0c70..0734758c4 100644 --- a/translations/fi/3-Web-App/1-Web-App/README.md +++ b/translations/fi/3-Web-App/1-Web-App/README.md @@ -1,12 +1,3 @@ - # Rakenna verkkosovellus ML-mallin käyttöön Tässä oppitunnissa koulutat ML-mallin datajoukolla, joka on kirjaimellisesti "maailman ulkopuolelta": _UFO-havainnot viimeisen vuosisadan ajalta_, jotka on kerätty NUFORC:n tietokannasta. diff --git a/translations/fi/3-Web-App/1-Web-App/assignment.md b/translations/fi/3-Web-App/1-Web-App/assignment.md index 92716c6b3..e7a569592 100644 --- a/translations/fi/3-Web-App/1-Web-App/assignment.md +++ b/translations/fi/3-Web-App/1-Web-App/assignment.md @@ -1,12 +1,3 @@ - # Kokeile eri mallia ## Ohjeet diff --git a/translations/fi/3-Web-App/README.md b/translations/fi/3-Web-App/README.md index b63e5b237..cdec49dd9 100644 --- a/translations/fi/3-Web-App/README.md +++ b/translations/fi/3-Web-App/README.md @@ -1,12 +1,3 @@ - # Rakenna verkkosovellus ML-mallisi käyttöön Tässä osiossa tutustut soveltavaan koneoppimisen aiheeseen: kuinka tallentaa Scikit-learn-malli tiedostoksi, jota voidaan käyttää ennusteiden tekemiseen verkkosovelluksessa. Kun malli on tallennettu, opit käyttämään sitä Flaskilla rakennetussa verkkosovelluksessa. Ensin luot mallin käyttäen dataa, joka liittyy UFO-havaintoihin! Sen jälkeen rakennat verkkosovelluksen, jonka avulla voit syöttää sekuntimäärän sekä leveys- ja pituusasteen arvot ennustaaksesi, mikä maa raportoi UFO-havainnon. diff --git a/translations/fi/4-Classification/1-Introduction/README.md b/translations/fi/4-Classification/1-Introduction/README.md index 5f6d27a78..43945999e 100644 --- a/translations/fi/4-Classification/1-Introduction/README.md +++ b/translations/fi/4-Classification/1-Introduction/README.md @@ -1,12 +1,3 @@ - # Johdanto luokitteluun Näissä neljässä oppitunnissa tutustut klassisen koneoppimisen keskeiseen osa-alueeseen - _luokitteluun_. Käymme läpi erilaisia luokittelualgoritmeja käyttäen datasettiä, joka käsittelee Aasian ja Intian upeita keittiöitä. Toivottavasti olet nälkäinen! diff --git a/translations/fi/4-Classification/1-Introduction/assignment.md b/translations/fi/4-Classification/1-Introduction/assignment.md index 6c9bb96be..945bf1ce4 100644 --- a/translations/fi/4-Classification/1-Introduction/assignment.md +++ b/translations/fi/4-Classification/1-Introduction/assignment.md @@ -1,12 +1,3 @@ - # Tutustu luokittelumenetelmiin ## Ohjeet diff --git a/translations/fi/4-Classification/1-Introduction/solution/Julia/README.md b/translations/fi/4-Classification/1-Introduction/solution/Julia/README.md index d5e32a914..aacb66189 100644 --- a/translations/fi/4-Classification/1-Introduction/solution/Julia/README.md +++ b/translations/fi/4-Classification/1-Introduction/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/fi/4-Classification/2-Classifiers-1/README.md b/translations/fi/4-Classification/2-Classifiers-1/README.md index ddb8aeedf..e4597a757 100644 --- a/translations/fi/4-Classification/2-Classifiers-1/README.md +++ b/translations/fi/4-Classification/2-Classifiers-1/README.md @@ -1,12 +1,3 @@ - # Ruokakulttuuriluokittelijat 1 Tässä oppitunnissa käytät edellisessä oppitunnissa tallentamaasi tasapainoista ja siistiä datasettiä, joka käsittelee ruokakulttuureja. diff --git a/translations/fi/4-Classification/2-Classifiers-1/assignment.md b/translations/fi/4-Classification/2-Classifiers-1/assignment.md index 9bdeab702..239d7dd9b 100644 --- a/translations/fi/4-Classification/2-Classifiers-1/assignment.md +++ b/translations/fi/4-Classification/2-Classifiers-1/assignment.md @@ -1,12 +1,3 @@ - # Tutustu ratkaisijoihin ## Ohjeet diff --git a/translations/fi/4-Classification/2-Classifiers-1/solution/Julia/README.md b/translations/fi/4-Classification/2-Classifiers-1/solution/Julia/README.md index cccd589ce..aacb66189 100644 --- a/translations/fi/4-Classification/2-Classifiers-1/solution/Julia/README.md +++ b/translations/fi/4-Classification/2-Classifiers-1/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/fi/4-Classification/3-Classifiers-2/README.md b/translations/fi/4-Classification/3-Classifiers-2/README.md index 976532873..0c9839a50 100644 --- a/translations/fi/4-Classification/3-Classifiers-2/README.md +++ b/translations/fi/4-Classification/3-Classifiers-2/README.md @@ -1,12 +1,3 @@ - # Ruokakulttuuriluokittelijat 2 Tässä toisessa luokittelutunnissa tutustut tarkemmin tapoihin luokitella numeerista dataa. Opit myös, mitä seurauksia on sillä, että valitset yhden luokittelijan toisen sijaan. diff --git a/translations/fi/4-Classification/3-Classifiers-2/assignment.md b/translations/fi/4-Classification/3-Classifiers-2/assignment.md index 7bea2b021..469d45e09 100644 --- a/translations/fi/4-Classification/3-Classifiers-2/assignment.md +++ b/translations/fi/4-Classification/3-Classifiers-2/assignment.md @@ -1,12 +1,3 @@ - # Parametrien säätö ## Ohjeet diff --git a/translations/fi/4-Classification/3-Classifiers-2/solution/Julia/README.md b/translations/fi/4-Classification/3-Classifiers-2/solution/Julia/README.md index 5455d0c0c..d9494a101 100644 --- a/translations/fi/4-Classification/3-Classifiers-2/solution/Julia/README.md +++ b/translations/fi/4-Classification/3-Classifiers-2/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/fi/4-Classification/4-Applied/README.md b/translations/fi/4-Classification/4-Applied/README.md index 3a6c235b2..eb38d50d5 100644 --- a/translations/fi/4-Classification/4-Applied/README.md +++ b/translations/fi/4-Classification/4-Applied/README.md @@ -1,12 +1,3 @@ - # Rakenna ruokasuositusverkkosovellus Tässä oppitunnissa rakennat luokittelumallin käyttäen joitakin aiemmissa oppitunneissa opittuja tekniikoita sekä herkullista ruokadatasettiä, jota on käytetty läpi tämän sarjan. Lisäksi rakennat pienen verkkosovelluksen, joka hyödyntää tallennettua mallia Onnxin verkkokäyttöliittymän avulla. diff --git a/translations/fi/4-Classification/4-Applied/assignment.md b/translations/fi/4-Classification/4-Applied/assignment.md index 436d58faa..adf73fbdf 100644 --- a/translations/fi/4-Classification/4-Applied/assignment.md +++ b/translations/fi/4-Classification/4-Applied/assignment.md @@ -1,12 +1,3 @@ - # Rakenna suosittelija ## Ohjeet diff --git a/translations/fi/4-Classification/README.md b/translations/fi/4-Classification/README.md index 8883c68fa..9f07b680a 100644 --- a/translations/fi/4-Classification/README.md +++ b/translations/fi/4-Classification/README.md @@ -1,12 +1,3 @@ - # Aloittaminen luokittelun parissa ## Alueellinen aihe: Herkulliset aasialaiset ja intialaiset ruoat 🍜 diff --git a/translations/fi/5-Clustering/1-Visualize/README.md b/translations/fi/5-Clustering/1-Visualize/README.md index 03458afc6..a509c4c42 100644 --- a/translations/fi/5-Clustering/1-Visualize/README.md +++ b/translations/fi/5-Clustering/1-Visualize/README.md @@ -1,12 +1,3 @@ - # Johdanto klusterointiin Klusterointi on eräänlainen [valvomaton oppiminen](https://wikipedia.org/wiki/Unsupervised_learning), joka olettaa, että datasetti on merkitsemätön tai että sen syötteet eivät ole yhdistetty ennalta määriteltyihin tuloksiin. Se käyttää erilaisia algoritmeja käydäkseen läpi merkitsemätöntä dataa ja luodakseen ryhmiä datasta havaittujen kuvioiden perusteella. diff --git a/translations/fi/5-Clustering/1-Visualize/assignment.md b/translations/fi/5-Clustering/1-Visualize/assignment.md index fe71f0958..a3eb15f98 100644 --- a/translations/fi/5-Clustering/1-Visualize/assignment.md +++ b/translations/fi/5-Clustering/1-Visualize/assignment.md @@ -1,12 +1,3 @@ - # Tutki muita visualisointitapoja klusterointia varten ## Ohjeet diff --git a/translations/fi/5-Clustering/1-Visualize/solution/Julia/README.md b/translations/fi/5-Clustering/1-Visualize/solution/Julia/README.md index 1e9c8d1bc..aacb66189 100644 --- a/translations/fi/5-Clustering/1-Visualize/solution/Julia/README.md +++ b/translations/fi/5-Clustering/1-Visualize/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/fi/5-Clustering/2-K-Means/README.md b/translations/fi/5-Clustering/2-K-Means/README.md index 505890dab..c9dea3af6 100644 --- a/translations/fi/5-Clustering/2-K-Means/README.md +++ b/translations/fi/5-Clustering/2-K-Means/README.md @@ -1,12 +1,3 @@ - # K-Means-klusterointi ## [Pre-lecture quiz](https://ff-quizzes.netlify.app/en/ml/) diff --git a/translations/fi/5-Clustering/2-K-Means/assignment.md b/translations/fi/5-Clustering/2-K-Means/assignment.md index 61784c342..efd594e01 100644 --- a/translations/fi/5-Clustering/2-K-Means/assignment.md +++ b/translations/fi/5-Clustering/2-K-Means/assignment.md @@ -1,12 +1,3 @@ - # Kokeile eri klusterointimenetelmiä ## Ohjeet diff --git a/translations/fi/5-Clustering/2-K-Means/solution/Julia/README.md b/translations/fi/5-Clustering/2-K-Means/solution/Julia/README.md index 7ed530ee2..aacb66189 100644 --- a/translations/fi/5-Clustering/2-K-Means/solution/Julia/README.md +++ b/translations/fi/5-Clustering/2-K-Means/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/fi/5-Clustering/README.md b/translations/fi/5-Clustering/README.md index 7ee454e4e..03ac7d8eb 100644 --- a/translations/fi/5-Clustering/README.md +++ b/translations/fi/5-Clustering/README.md @@ -1,12 +1,3 @@ - # Klusterointimallit koneoppimiseen Klusterointi on koneoppimisen tehtävä, jossa pyritään löytämään toisiaan muistuttavia objekteja ja ryhmittelemään ne ryhmiin, joita kutsutaan klustereiksi. Se, mikä erottaa klusteroinnin muista koneoppimisen lähestymistavoista, on se, että prosessi tapahtuu automaattisesti. Itse asiassa voidaan sanoa, että se on päinvastainen valvotulle oppimiselle. diff --git a/translations/fi/6-NLP/1-Introduction-to-NLP/README.md b/translations/fi/6-NLP/1-Introduction-to-NLP/README.md index 9ea31ebcf..eab3b7a0c 100644 --- a/translations/fi/6-NLP/1-Introduction-to-NLP/README.md +++ b/translations/fi/6-NLP/1-Introduction-to-NLP/README.md @@ -1,12 +1,3 @@ - # Johdatus luonnollisen kielen käsittelyyn Tässä oppitunnissa käsitellään lyhyesti *luonnollisen kielen käsittelyn* historiaa ja keskeisiä käsitteitä, joka on osa-alue *laskennallisesta kielitieteestä*. diff --git a/translations/fi/6-NLP/1-Introduction-to-NLP/assignment.md b/translations/fi/6-NLP/1-Introduction-to-NLP/assignment.md index 3e4b20b96..596479c0b 100644 --- a/translations/fi/6-NLP/1-Introduction-to-NLP/assignment.md +++ b/translations/fi/6-NLP/1-Introduction-to-NLP/assignment.md @@ -1,12 +1,3 @@ - # Etsi botti ## Ohjeet diff --git a/translations/fi/6-NLP/2-Tasks/README.md b/translations/fi/6-NLP/2-Tasks/README.md index 2864e0705..69d208ce1 100644 --- a/translations/fi/6-NLP/2-Tasks/README.md +++ b/translations/fi/6-NLP/2-Tasks/README.md @@ -1,12 +1,3 @@ - # Yleisiä luonnollisen kielen käsittelyn tehtäviä ja tekniikoita Useimmissa *luonnollisen kielen käsittelyn* tehtävissä käsiteltävä teksti täytyy pilkkoa, tutkia ja tallentaa tulokset tai verrata niitä sääntöihin ja tietokantoihin. Näiden tehtävien avulla ohjelmoija voi selvittää tekstin _merkityksen_, _tarkoituksen_ tai pelkästään _sanojen ja termien esiintymistiheyden_. diff --git a/translations/fi/6-NLP/2-Tasks/assignment.md b/translations/fi/6-NLP/2-Tasks/assignment.md index 2e7d1eaab..1201a395a 100644 --- a/translations/fi/6-NLP/2-Tasks/assignment.md +++ b/translations/fi/6-NLP/2-Tasks/assignment.md @@ -1,12 +1,3 @@ - # Tee botista vastaava ## Ohjeet diff --git a/translations/fi/6-NLP/3-Translation-Sentiment/README.md b/translations/fi/6-NLP/3-Translation-Sentiment/README.md index a35e1e5c2..76f9dd421 100644 --- a/translations/fi/6-NLP/3-Translation-Sentiment/README.md +++ b/translations/fi/6-NLP/3-Translation-Sentiment/README.md @@ -1,12 +1,3 @@ - # Käännös ja sentimenttianalyysi koneoppimisen avulla Aiemmissa oppitunneissa opit rakentamaan yksinkertaisen botin käyttämällä `TextBlob`-kirjastoa, joka hyödyntää koneoppimista taustalla suorittaakseen perusluonteisia luonnollisen kielen käsittelytehtäviä, kuten substantiivilauseiden tunnistamista. Toinen tärkeä haaste laskennallisessa kielitieteessä on lauseen tarkka _kääntäminen_ yhdestä puhutuista tai kirjoitetuista kielistä toiseen. diff --git a/translations/fi/6-NLP/3-Translation-Sentiment/assignment.md b/translations/fi/6-NLP/3-Translation-Sentiment/assignment.md index e1a87076b..f3b65893e 100644 --- a/translations/fi/6-NLP/3-Translation-Sentiment/assignment.md +++ b/translations/fi/6-NLP/3-Translation-Sentiment/assignment.md @@ -1,12 +1,3 @@ - # Runollinen vapaus ## Ohjeet diff --git a/translations/fi/6-NLP/3-Translation-Sentiment/solution/Julia/README.md b/translations/fi/6-NLP/3-Translation-Sentiment/solution/Julia/README.md index b80a3bec7..aacb66189 100644 --- a/translations/fi/6-NLP/3-Translation-Sentiment/solution/Julia/README.md +++ b/translations/fi/6-NLP/3-Translation-Sentiment/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/fi/6-NLP/3-Translation-Sentiment/solution/R/README.md b/translations/fi/6-NLP/3-Translation-Sentiment/solution/R/README.md index 7ef8db698..e8a03824e 100644 --- a/translations/fi/6-NLP/3-Translation-Sentiment/solution/R/README.md +++ b/translations/fi/6-NLP/3-Translation-Sentiment/solution/R/README.md @@ -1,12 +1,3 @@ - tämä on väliaikainen paikkamerkki --- diff --git a/translations/fi/6-NLP/4-Hotel-Reviews-1/README.md b/translations/fi/6-NLP/4-Hotel-Reviews-1/README.md index 9332aeaa4..ba2402039 100644 --- a/translations/fi/6-NLP/4-Hotel-Reviews-1/README.md +++ b/translations/fi/6-NLP/4-Hotel-Reviews-1/README.md @@ -1,12 +1,3 @@ - # Sentimenttianalyysi hotelliarvosteluilla - datan käsittely Tässä osiossa käytät aiemmissa oppitunneissa opittuja tekniikoita suuren datasetin tutkimiseen. Kun ymmärrät eri sarakkeiden hyödyllisyyden, opit: diff --git a/translations/fi/6-NLP/4-Hotel-Reviews-1/assignment.md b/translations/fi/6-NLP/4-Hotel-Reviews-1/assignment.md index c2c3c53f7..3e3cc4016 100644 --- a/translations/fi/6-NLP/4-Hotel-Reviews-1/assignment.md +++ b/translations/fi/6-NLP/4-Hotel-Reviews-1/assignment.md @@ -1,12 +1,3 @@ - # NLTK ## Ohjeet diff --git a/translations/fi/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md b/translations/fi/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md index 5bfc0026c..d9494a101 100644 --- a/translations/fi/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md +++ b/translations/fi/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/fi/6-NLP/4-Hotel-Reviews-1/solution/R/README.md b/translations/fi/6-NLP/4-Hotel-Reviews-1/solution/R/README.md index 8d2de9650..b796d5aa0 100644 --- a/translations/fi/6-NLP/4-Hotel-Reviews-1/solution/R/README.md +++ b/translations/fi/6-NLP/4-Hotel-Reviews-1/solution/R/README.md @@ -1,12 +1,3 @@ - tämä on väliaikainen paikkamerkki --- diff --git a/translations/fi/6-NLP/5-Hotel-Reviews-2/README.md b/translations/fi/6-NLP/5-Hotel-Reviews-2/README.md index f6f85563e..775b563c9 100644 --- a/translations/fi/6-NLP/5-Hotel-Reviews-2/README.md +++ b/translations/fi/6-NLP/5-Hotel-Reviews-2/README.md @@ -1,12 +1,3 @@ - # Mielipiteiden analysointi hotelliarvosteluista Nyt kun olet tutkinut datasettiä yksityiskohtaisesti, on aika suodattaa sarakkeita ja käyttää NLP-tekniikoita datasetissä saadaksesi uusia näkemyksiä hotelleista. diff --git a/translations/fi/6-NLP/5-Hotel-Reviews-2/assignment.md b/translations/fi/6-NLP/5-Hotel-Reviews-2/assignment.md index 3d3157fcd..d8639a91c 100644 --- a/translations/fi/6-NLP/5-Hotel-Reviews-2/assignment.md +++ b/translations/fi/6-NLP/5-Hotel-Reviews-2/assignment.md @@ -1,12 +1,3 @@ - # Kokeile eri datasettiä ## Ohjeet diff --git a/translations/fi/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md b/translations/fi/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md index a777264be..aacb66189 100644 --- a/translations/fi/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md +++ b/translations/fi/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/fi/6-NLP/5-Hotel-Reviews-2/solution/R/README.md b/translations/fi/6-NLP/5-Hotel-Reviews-2/solution/R/README.md index 8477ade14..b796d5aa0 100644 --- a/translations/fi/6-NLP/5-Hotel-Reviews-2/solution/R/README.md +++ b/translations/fi/6-NLP/5-Hotel-Reviews-2/solution/R/README.md @@ -1,12 +1,3 @@ - tämä on väliaikainen paikkamerkki --- diff --git a/translations/fi/6-NLP/README.md b/translations/fi/6-NLP/README.md index dd00d3182..0aa4dca45 100644 --- a/translations/fi/6-NLP/README.md +++ b/translations/fi/6-NLP/README.md @@ -1,12 +1,3 @@ - # Aloittaminen luonnollisen kielen käsittelyssä Luonnollisen kielen käsittely (NLP) tarkoittaa tietokoneohjelman kykyä ymmärtää ihmisen kieltä sellaisena kuin sitä puhutaan ja kirjoitetaan – eli luonnollisena kielenä. Se on osa tekoälyä (AI). NLP on ollut olemassa yli 50 vuotta ja sillä on juuret kielitieteen alalla. Koko ala keskittyy auttamaan koneita ymmärtämään ja käsittelemään ihmisen kieltä. Tätä voidaan käyttää tehtäviin, kuten oikeinkirjoituksen tarkistukseen tai konekäännökseen. NLP:llä on monia käytännön sovelluksia eri aloilla, kuten lääketieteellisessä tutkimuksessa, hakukoneissa ja liiketoimintatiedon analysoinnissa. diff --git a/translations/fi/6-NLP/data/README.md b/translations/fi/6-NLP/data/README.md index 807be0d97..77ce00e02 100644 --- a/translations/fi/6-NLP/data/README.md +++ b/translations/fi/6-NLP/data/README.md @@ -1,12 +1,3 @@ - Lataa hotelliarvosteludata tähän kansioon. --- diff --git a/translations/fi/7-TimeSeries/1-Introduction/README.md b/translations/fi/7-TimeSeries/1-Introduction/README.md index 43a0b3400..516b4b908 100644 --- a/translations/fi/7-TimeSeries/1-Introduction/README.md +++ b/translations/fi/7-TimeSeries/1-Introduction/README.md @@ -1,12 +1,3 @@ - # Johdanto aikasarjojen ennustamiseen ![Yhteenveto aikasarjoista sketchnotessa](../../../../sketchnotes/ml-timeseries.png) diff --git a/translations/fi/7-TimeSeries/1-Introduction/assignment.md b/translations/fi/7-TimeSeries/1-Introduction/assignment.md index dc508e712..d3c7e82f4 100644 --- a/translations/fi/7-TimeSeries/1-Introduction/assignment.md +++ b/translations/fi/7-TimeSeries/1-Introduction/assignment.md @@ -1,12 +1,3 @@ - # Visualisoi lisää aikasarjoja ## Ohjeet diff --git a/translations/fi/7-TimeSeries/1-Introduction/solution/Julia/README.md b/translations/fi/7-TimeSeries/1-Introduction/solution/Julia/README.md index 186ce79d7..d9494a101 100644 --- a/translations/fi/7-TimeSeries/1-Introduction/solution/Julia/README.md +++ b/translations/fi/7-TimeSeries/1-Introduction/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/fi/7-TimeSeries/1-Introduction/solution/R/README.md b/translations/fi/7-TimeSeries/1-Introduction/solution/R/README.md index b0b8094fa..b796d5aa0 100644 --- a/translations/fi/7-TimeSeries/1-Introduction/solution/R/README.md +++ b/translations/fi/7-TimeSeries/1-Introduction/solution/R/README.md @@ -1,12 +1,3 @@ - tämä on väliaikainen paikkamerkki --- diff --git a/translations/fi/7-TimeSeries/2-ARIMA/README.md b/translations/fi/7-TimeSeries/2-ARIMA/README.md index 7df47533d..75546bda8 100644 --- a/translations/fi/7-TimeSeries/2-ARIMA/README.md +++ b/translations/fi/7-TimeSeries/2-ARIMA/README.md @@ -1,12 +1,3 @@ - # Aikasarjojen ennustaminen ARIMA-mallilla Edellisessä oppitunnissa opit hieman aikasarjojen ennustamisesta ja latasit tietoaineiston, joka näyttää sähkönkulutuksen vaihtelut tietyn ajanjakson aikana. diff --git a/translations/fi/7-TimeSeries/2-ARIMA/assignment.md b/translations/fi/7-TimeSeries/2-ARIMA/assignment.md index f5dabc4ef..fa01403af 100644 --- a/translations/fi/7-TimeSeries/2-ARIMA/assignment.md +++ b/translations/fi/7-TimeSeries/2-ARIMA/assignment.md @@ -1,12 +1,3 @@ - # Uusi ARIMA-malli ## Ohjeet diff --git a/translations/fi/7-TimeSeries/2-ARIMA/solution/Julia/README.md b/translations/fi/7-TimeSeries/2-ARIMA/solution/Julia/README.md index bd4337350..aacb66189 100644 --- a/translations/fi/7-TimeSeries/2-ARIMA/solution/Julia/README.md +++ b/translations/fi/7-TimeSeries/2-ARIMA/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/fi/7-TimeSeries/2-ARIMA/solution/R/README.md b/translations/fi/7-TimeSeries/2-ARIMA/solution/R/README.md index b2287da99..b796d5aa0 100644 --- a/translations/fi/7-TimeSeries/2-ARIMA/solution/R/README.md +++ b/translations/fi/7-TimeSeries/2-ARIMA/solution/R/README.md @@ -1,12 +1,3 @@ - tämä on väliaikainen paikkamerkki --- diff --git a/translations/fi/7-TimeSeries/3-SVR/README.md b/translations/fi/7-TimeSeries/3-SVR/README.md index 3ba1bcda4..41a32c5a2 100644 --- a/translations/fi/7-TimeSeries/3-SVR/README.md +++ b/translations/fi/7-TimeSeries/3-SVR/README.md @@ -1,12 +1,3 @@ - # Aikasarjojen ennustaminen Support Vector Regressor -mallilla Edellisessä osiossa opit käyttämään ARIMA-mallia aikasarjojen ennustamiseen. Nyt tutustut Support Vector Regressor -malliin, joka on regressiomalli jatkuvien arvojen ennustamiseen. diff --git a/translations/fi/7-TimeSeries/3-SVR/assignment.md b/translations/fi/7-TimeSeries/3-SVR/assignment.md index 487b3444a..4f42e44d7 100644 --- a/translations/fi/7-TimeSeries/3-SVR/assignment.md +++ b/translations/fi/7-TimeSeries/3-SVR/assignment.md @@ -1,12 +1,3 @@ - # Uusi SVR-malli ## Ohjeet [^1] diff --git a/translations/fi/7-TimeSeries/README.md b/translations/fi/7-TimeSeries/README.md index bb37ed7d3..b04f16896 100644 --- a/translations/fi/7-TimeSeries/README.md +++ b/translations/fi/7-TimeSeries/README.md @@ -1,12 +1,3 @@ - # Johdatus aikasarjojen ennustamiseen Mitä aikasarjojen ennustaminen on? Kyse on tulevien tapahtumien ennustamisesta analysoimalla menneitä trendejä. diff --git a/translations/fi/8-Reinforcement/1-QLearning/README.md b/translations/fi/8-Reinforcement/1-QLearning/README.md index fdbf56643..127ccebb9 100644 --- a/translations/fi/8-Reinforcement/1-QLearning/README.md +++ b/translations/fi/8-Reinforcement/1-QLearning/README.md @@ -1,12 +1,3 @@ - # Johdanto vahvistusoppimiseen ja Q-oppimiseen ![Yhteenveto vahvistusoppimisesta koneoppimisessa sketchnotena](../../../../sketchnotes/ml-reinforcement.png) diff --git a/translations/fi/8-Reinforcement/1-QLearning/assignment.md b/translations/fi/8-Reinforcement/1-QLearning/assignment.md index a391a1e9a..ad3a7eade 100644 --- a/translations/fi/8-Reinforcement/1-QLearning/assignment.md +++ b/translations/fi/8-Reinforcement/1-QLearning/assignment.md @@ -1,12 +1,3 @@ - # Realistisempi maailma Meidän tilanteessamme Peter pystyi liikkumaan lähes väsymättä tai tuntematta nälkää. Realistisemmassa maailmassa hänen täytyy välillä istua alas ja levätä, sekä syödä jotain. Tehdään maailmastamme realistisempi toteuttamalla seuraavat säännöt: diff --git a/translations/fi/8-Reinforcement/1-QLearning/solution/Julia/README.md b/translations/fi/8-Reinforcement/1-QLearning/solution/Julia/README.md index df4637a54..d9494a101 100644 --- a/translations/fi/8-Reinforcement/1-QLearning/solution/Julia/README.md +++ b/translations/fi/8-Reinforcement/1-QLearning/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/fi/8-Reinforcement/1-QLearning/solution/R/README.md b/translations/fi/8-Reinforcement/1-QLearning/solution/R/README.md index 6b392cc7a..e8a03824e 100644 --- a/translations/fi/8-Reinforcement/1-QLearning/solution/R/README.md +++ b/translations/fi/8-Reinforcement/1-QLearning/solution/R/README.md @@ -1,12 +1,3 @@ - tämä on väliaikainen paikkamerkki --- diff --git a/translations/fi/8-Reinforcement/2-Gym/README.md b/translations/fi/8-Reinforcement/2-Gym/README.md index d6ea0080d..eb77286c5 100644 --- a/translations/fi/8-Reinforcement/2-Gym/README.md +++ b/translations/fi/8-Reinforcement/2-Gym/README.md @@ -1,12 +1,3 @@ - ## Esivaatimukset Tässä oppitunnissa käytämme kirjastoa nimeltä **OpenAI Gym** simuloimaan erilaisia **ympäristöjä**. Voit ajaa oppitunnin koodin paikallisesti (esim. Visual Studio Codessa), jolloin simulaatio avautuu uuteen ikkunaan. Jos suoritat koodin verkossa, sinun täytyy ehkä tehdä joitakin muutoksia koodiin, kuten kuvataan [tässä](https://towardsdatascience.com/rendering-openai-gym-envs-on-binder-and-google-colab-536f99391cc7). diff --git a/translations/fi/8-Reinforcement/2-Gym/assignment.md b/translations/fi/8-Reinforcement/2-Gym/assignment.md index 7dec023e6..124188377 100644 --- a/translations/fi/8-Reinforcement/2-Gym/assignment.md +++ b/translations/fi/8-Reinforcement/2-Gym/assignment.md @@ -1,12 +1,3 @@ - # Kouluta Mountain Car [OpenAI Gym](http://gym.openai.com) on suunniteltu siten, että kaikki ympäristöt tarjoavat saman API:n - eli samat metodit `reset`, `step` ja `render`, sekä samat abstraktiot **toimintatilasta** ja **havaintotilasta**. Näin ollen pitäisi olla mahdollista soveltaa samoja vahvistusoppimisalgoritmeja eri ympäristöihin vähäisin koodimuutoksin. diff --git a/translations/fi/8-Reinforcement/2-Gym/solution/Julia/README.md b/translations/fi/8-Reinforcement/2-Gym/solution/Julia/README.md index 9b55a5500..d9494a101 100644 --- a/translations/fi/8-Reinforcement/2-Gym/solution/Julia/README.md +++ b/translations/fi/8-Reinforcement/2-Gym/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/fi/8-Reinforcement/2-Gym/solution/R/README.md b/translations/fi/8-Reinforcement/2-Gym/solution/R/README.md index 652affa7b..b796d5aa0 100644 --- a/translations/fi/8-Reinforcement/2-Gym/solution/R/README.md +++ b/translations/fi/8-Reinforcement/2-Gym/solution/R/README.md @@ -1,12 +1,3 @@ - tämä on väliaikainen paikkamerkki --- diff --git a/translations/fi/8-Reinforcement/README.md b/translations/fi/8-Reinforcement/README.md index d78e967fc..836040973 100644 --- a/translations/fi/8-Reinforcement/README.md +++ b/translations/fi/8-Reinforcement/README.md @@ -1,12 +1,3 @@ - # Johdatus vahvistusoppimiseen Vahvistusoppiminen, RL, nähdään yhtenä koneoppimisen perusparadigmoista, yhdessä ohjatun oppimisen ja ohjaamattoman oppimisen kanssa. RL keskittyy päätöksentekoon: oikeiden päätösten tekemiseen tai ainakin oppimiseen niistä. diff --git a/translations/fi/9-Real-World/1-Applications/README.md b/translations/fi/9-Real-World/1-Applications/README.md index 8a72d4a22..04d412f27 100644 --- a/translations/fi/9-Real-World/1-Applications/README.md +++ b/translations/fi/9-Real-World/1-Applications/README.md @@ -1,12 +1,3 @@ - # Jälkikirjoitus: Koneoppiminen tosielämässä ![Yhteenveto koneoppimisesta tosielämässä sketchnotessa](../../../../sketchnotes/ml-realworld.png) diff --git a/translations/fi/9-Real-World/1-Applications/assignment.md b/translations/fi/9-Real-World/1-Applications/assignment.md index 008472b94..577b126a2 100644 --- a/translations/fi/9-Real-World/1-Applications/assignment.md +++ b/translations/fi/9-Real-World/1-Applications/assignment.md @@ -1,12 +1,3 @@ - # ML-aarteenetsintä ## Ohjeet diff --git a/translations/fi/9-Real-World/2-Debugging-ML-Models/README.md b/translations/fi/9-Real-World/2-Debugging-ML-Models/README.md index 4d7067e41..44e31195f 100644 --- a/translations/fi/9-Real-World/2-Debugging-ML-Models/README.md +++ b/translations/fi/9-Real-World/2-Debugging-ML-Models/README.md @@ -1,12 +1,3 @@ - # Jälkikirjoitus: Mallin virheenkorjaus koneoppimisessa vastuullisen tekoälyn hallintapaneelin komponenttien avulla ## [Esiluennon kysely](https://ff-quizzes.netlify.app/en/ml/) diff --git a/translations/fi/9-Real-World/2-Debugging-ML-Models/assignment.md b/translations/fi/9-Real-World/2-Debugging-ML-Models/assignment.md index e4e656ce6..3c082c755 100644 --- a/translations/fi/9-Real-World/2-Debugging-ML-Models/assignment.md +++ b/translations/fi/9-Real-World/2-Debugging-ML-Models/assignment.md @@ -1,12 +1,3 @@ - # Tutustu vastuullisen tekoälyn (RAI) hallintapaneeliin ## Ohjeet diff --git a/translations/fi/9-Real-World/README.md b/translations/fi/9-Real-World/README.md index 98deac298..fdd76fcb9 100644 --- a/translations/fi/9-Real-World/README.md +++ b/translations/fi/9-Real-World/README.md @@ -1,12 +1,3 @@ - # Jälkikirjoitus: Klassisen koneoppimisen todelliset sovellukset Tässä osiossa tutustut klassisen koneoppimisen todellisiin sovelluksiin. Olemme etsineet internetistä tutkimusartikkeleita ja kirjoituksia sovelluksista, joissa on käytetty näitä strategioita, välttäen mahdollisimman paljon neuroverkkoja, syväoppimista ja tekoälyä. Opit, miten koneoppimista hyödynnetään liiketoimintajärjestelmissä, ekologisissa sovelluksissa, rahoituksessa, taiteessa ja kulttuurissa sekä muilla aloilla. diff --git a/translations/fi/AGENTS.md b/translations/fi/AGENTS.md index 36fa1f21f..8b8a9e2c4 100644 --- a/translations/fi/AGENTS.md +++ b/translations/fi/AGENTS.md @@ -1,12 +1,3 @@ - # AGENTS.md ## Projektin yleiskuvaus diff --git a/translations/fi/CODE_OF_CONDUCT.md b/translations/fi/CODE_OF_CONDUCT.md index 35dffef27..25d925b76 100644 --- a/translations/fi/CODE_OF_CONDUCT.md +++ b/translations/fi/CODE_OF_CONDUCT.md @@ -1,12 +1,3 @@ - # Microsoftin avoimen lähdekoodin toimintaohjeet Tämä projekti on ottanut käyttöön [Microsoftin avoimen lähdekoodin toimintaohjeet](https://opensource.microsoft.com/codeofconduct/). diff --git a/translations/fi/CONTRIBUTING.md b/translations/fi/CONTRIBUTING.md index fd333700f..527ed7e0a 100644 --- a/translations/fi/CONTRIBUTING.md +++ b/translations/fi/CONTRIBUTING.md @@ -1,12 +1,3 @@ - # Osallistuminen Tämä projekti toivottaa tervetulleeksi osallistumiset ja ehdotukset. Useimmat osallistumiset edellyttävät, että hyväksyt Contributor License Agreementin (CLA), jossa vakuutat, että sinulla on oikeus antaa meille oikeudet käyttää panostasi. Lisätietoja löydät osoitteesta https://cla.microsoft.com. diff --git a/translations/fi/README.md b/translations/fi/README.md index da892406c..5beb04ca9 100644 --- a/translations/fi/README.md +++ b/translations/fi/README.md @@ -1,100 +1,91 @@ - -[![GitHub-lisenssi](https://img.shields.io/github/license/microsoft/ML-For-Beginners.svg)](https://github.com/microsoft/ML-For-Beginners/blob/master/LICENSE) -[![GitHub-avustajat](https://img.shields.io/github/contributors/microsoft/ML-For-Beginners.svg)](https://GitHub.com/microsoft/ML-For-Beginners/graphs/contributors/) -[![GitHub-ongelmat](https://img.shields.io/github/issues/microsoft/ML-For-Beginners.svg)](https://GitHub.com/microsoft/ML-For-Beginners/issues/) -[![GitHub pull-pyynnöt](https://img.shields.io/github/issues-pr/microsoft/ML-For-Beginners.svg)](https://GitHub.com/microsoft/ML-For-Beginners/pulls/) -[![PR:t tervetulleita](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com) - -[![GitHub-seuraajat](https://img.shields.io/github/watchers/microsoft/ML-For-Beginners.svg?style=social&label=Watch)](https://GitHub.com/microsoft/ML-For-Beginners/watchers/) -[![GitHub haarukat](https://img.shields.io/github/forks/microsoft/ML-For-Beginners.svg?style=social&label=Fork)](https://GitHub.com/microsoft/ML-For-Beginners/network/) -[![GitHub tähdet](https://img.shields.io/github/stars/microsoft/ML-For-Beginners.svg?style=social&label=Star)](https://GitHub.com/microsoft/ML-For-Beginners/stargazers/) +[![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/) +[![GitHub pull-requests](https://img.shields.io/github/issues-pr/microsoft/ML-For-Beginners.svg)](https://GitHub.com/microsoft/ML-For-Beginners/pulls/) +[![PRs Welcome](https://img.shields.io/badge/PRs-welcome-brightgreen.svg?style=flat-square)](http://makeapullrequest.com) + +[![GitHub watchers](https://img.shields.io/github/watchers/microsoft/ML-For-Beginners.svg?style=social&label=Watch)](https://GitHub.com/microsoft/ML-For-Beginners/watchers/) +[![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/) ### 🌐 Monikielinen tuki -#### Tuettu GitHub Actionin avulla (automaattinen & aina ajan tasalla) +#### Tuettu GitHub Actionin kautta (automaattinen ja aina ajan tasalla) -[Arabia](../ar/README.md) | [Bengali](../bn/README.md) | [Bulgaria](../bg/README.md) | [Burma (Myanmar)](../my/README.md) | [Kiina (yksinkertaistettu)](../zh/README.md) | [Kiina (perinteinen, Hong Kong)](../hk/README.md) | [Kiina (perinteinen, Macau)](../mo/README.md) | [Kiina (perinteinen, Taiwan)](../tw/README.md) | [Kroatia](../hr/README.md) | [Tšekki](../cs/README.md) | [Tanska](../da/README.md) | [Hollanti](../nl/README.md) | [Viro](../et/README.md) | [Suomi](./README.md) | [Ranska](../fr/README.md) | [Saksa](../de/README.md) | [Kreikka](../el/README.md) | [Heprea](../he/README.md) | [Hindi](../hi/README.md) | [Unkari](../hu/README.md) | [Indonesia](../id/README.md) | [Italia](../it/README.md) | [Japani](../ja/README.md) | [Kannada](../kn/README.md) | [Korea](../ko/README.md) | [Liettua](../lt/README.md) | [Malaiji](../ms/README.md) | [Malajalam](../ml/README.md) | [Marathi](../mr/README.md) | [Nepali](../ne/README.md) | [Nigerian Pidgin](../pcm/README.md) | [Norja](../no/README.md) | [Persia (Farsi)](../fa/README.md) | [Puola](../pl/README.md) | [Portugali (Brasilia)](../br/README.md) | [Portugali (Portugali)](../pt/README.md) | [Punjabi (Gurmukhi)](../pa/README.md) | [Romania](../ro/README.md) | [Venäjä](../ru/README.md) | [Serbia (kyrillinen)](../sr/README.md) | [Slovakki](../sk/README.md) | [Sloveeni](../sl/README.md) | [Espanja](../es/README.md) | [Swahili](../sw/README.md) | [Ruotsi](../sv/README.md) | [Tagalog (Filipino)](../tl/README.md) | [Tamil](../ta/README.md) | [Telugu](../te/README.md) | [Thai](../th/README.md) | [Turkki](../tr/README.md) | [Ukraina](../uk/README.md) | [Urdu](../ur/README.md) | [Vietnam](../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](./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)](../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) > **Haluatko mieluummin kloonata paikallisesti?** -> Tämä repositorio sisältää yli 50 kielen käännökset, mikä kasvattaa latauskokoa merkittävästi. Jos haluat kloonata ilman käännöksiä, käytä harvaa checkoutia: +> Tämä repositorio sisältää yli 50 kielen käännöksiä, mikä lisää latauskoon huomattavasti. Jotta voit kloonata ilman käännöksiä, käytä sparse checkout -toimintoa: > ```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' > ``` -> Tämä tarjoaa kaiken tarvittavan kurssin suorittamiseen huomattavasti nopeammalla latauksella. +> Tämä antaa sinulle kaiken tarvittavan kurssin suorittamiseen huomattavasti nopeammalla latauksella. #### Liity yhteisöömme [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -Meillä on käynnissä Discordin Learn with AI -sarja, opi lisää ja liity mukaan osoitteessa [Learn with AI Series](https://aka.ms/learnwithai/discord) 18. – 30. syyskuuta 2025. Saat vinkkejä ja temppuja GitHub Copilotin käyttämiseen Data Scienticessä. +Meillä on käynnissä Discordin Learn with AI -sarja, lue lisää ja liity mukaan osoitteessa [Learn with AI Series](https://aka.ms/learnwithai/discord) 18. – 30. syyskuuta 2025. Saat vinkkejä ja niksejä GitHub Copilotin käytöstä Data Scienceen. -![Learn with AI series](../../../../translated_images/fi/3.9b58fd8d6c373c20.webp) +![Learn with AI series](../../translated_images/fi/3.9b58fd8d6c373c20.webp) -# Koneoppiminen aloittelijoille – opetussuunnitelma +# Koneoppiminen aloittelijoille – opintokokonaisuus -> 🌍 Matkusta ympäri maailmaa tutkiskellessamme koneoppimista maailman kulttuurien kautta 🌍 +> 🌍 Matkusta ympäri maailmaa tutkiessamme koneoppimista maailman kulttuurien kautta 🌍 -Microsoftin Cloud Advocates tarjoaa 12 viikon ja 26 oppitunnin opetussuunnitelman, joka käsittelee **koneoppimista**. Tässä opetussuunnitelmassa opit siitä, mitä joskus kutsutaan **klassiseksi koneoppimiseksi**, pääasiassa Scikit-learn-kirjastoa käyttäen ja välttäen syväoppimista, joka käsitellään [AI for Beginners -opetussuunnitelmassamme](https://aka.ms/ai4beginners). Yhdistä nämä oppitunnit myös ['Data Science for Beginners' -opetussuunnitelmaamme](https://aka.ms/ds4beginners)! +Microsoftin Cloud Advocates -tiimi tarjoaa 12 viikon, 26 oppitunnin opintokokonaisuuden, joka käsittelee **koneoppimista**. Tässä opintokokonaisuudessa opit niin kutsuttua **klassista koneoppimista**, käyttäen pääasiallisesti Scikit-learn-kirjastoa ja välttäen syväoppimista, joka käsitellään [AI for Beginners -opintokokonaisuudessamme](https://aka.ms/ai4beginners). Yhdistä nämä oppitunnit myös ['Data Science for Beginners' -opintokokonaisuuteen](https://aka.ms/ds4beginners)! -Matkusta kanssamme ympäri maailmaa soveltaen näitä klassisia tekniikoita eri alueiden dataan. Jokainen oppitunti sisältää ennakko- ja jälkikäteen suoritettavat testit, kirjalliset ohjeet oppitunnin suorittamiseen, ratkaisun, tehtävän ja muuta. Projektipohjainen pedagogiikkamme mahdollistaa oppimisen rakentamisen kautta, mikä on todistettu tapa omaksua uusia taitoja. +Matkusta kanssamme ympäri maailmaa soveltaen klassisia tekniikoita datalla eri puolilta maailmaa. Jokainen oppitunti sisältää ennakko- ja jälkikäteen tehtävät visailut, kirjalliset ohjeet oppitunnin suorittamiseen, ratkaisun, tehtävän ja paljon muuta. Projektipohjainen pedagogiikkamme antaa mahdollisuuden oppia rakentamalla, mikä on todettu tehokkaaksi tavaksi oppia uusia taitoja. -**✍️ Suuret kiitokset kirjoittajillemme** Jen Looper, Stephen Howell, Francesca Lazzeri, Tomomi Imura, Cassie Breviu, Dmitry Soshnikov, Chris Noring, Anirban Mukherjee, Ornella Altunyan, Ruth Yakubu ja Amy Boyd +**✍️ Suuret kiitokset kirjoittajillemme:** Jen Looper, Stephen Howell, Francesca Lazzeri, Tomomi Imura, Cassie Breviu, Dmitry Soshnikov, Chris Noring, Anirban Mukherjee, Ornella Altunyan, Ruth Yakubu ja Amy Boyd -**🎨 Kiitos myös kuvittajillemme** Tomomi Imura, Dasani Madipalli ja Jen Looper +**🎨 Kiitokset myös kuvittajille:** Tomomi Imura, Dasani Madipalli ja Jen Looper -**🙏 Erityiskiitos 🙏 Microsoft Student Ambassador -kirjoittajille, arvioijille ja sisällöntuottajillemme**, erityisesti Rishit Dagli, Muhammad Sakib Khan Inan, Rohan Raj, Alexandru Petrescu, Abhishek Jaiswal, Nawrin Tabassum, Ioan Samuila ja Snigdha Agarwal +**🙏 Erityiskiitos 🙏 Microsoftin opiskelijaelävöittäjille, kirjoittajille, arvostelijoille ja sisällön tuottajille**, erityisesti Rishit Dagli, Muhammad Sakib Khan Inan, Rohan Raj, Alexandru Petrescu, Abhishek Jaiswal, Nawrin Tabassum, Ioan Samuila ja Snigdha Agarwal -**🤩 Lisäkiitos Microsoft Student Ambassadors Eric Wanjau, Jasleen Sondhi ja Vidushi Gupta R-oppitunneistamme!** +**🤩 Erityiskiitos Microsoftin opiskelijaelävöittäjille Eric Wanjau, Jasleen Sondhi ja Vidushi Gupta R-opetuskertojemme tukemisesta!** -# Aloittaminen +# Aloita tästä Seuraa näitä ohjeita: -1. **Forkkaa repositorio**: Klikkaa oikeassa yläkulmassa olevaa "Fork"-painiketta. -2. **Kloonaa repositorio**: `git clone https://github.com/microsoft/ML-For-Beginners.git` +1. **Forkkaa repositorio**: Klikkaa sivun oikeasta yläkulmasta "Fork" -painiketta. +2. **Kloonaa repositorio**: `git clone https://github.com/microsoft/ML-For-Beginners.git` -> [löydät kaikki kurssin lisäresurssit Microsoft Learn -kokoelmastamme](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) +> [Löydät kaikki lisäresurssit tälle kurssille Microsoft Learn -kokoelmastamme](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) -> 🔧 **Tarvitsetko apua?** Tarkista [Vianmääritysohjeistuksemme](TROUBLESHOOTING.md) yleisiin asennus-, käyttöönotto- ja oppituntien suorittamisen ongelmiin. +> 🔧 **Tarvitsetko apua?** Katso [Vianmääritysohje](TROUBLESHOOTING.md) yleisimpien asennus-, käyttöönotto- ja oppituntien ajamiseen liittyvien ongelmien ratkaisuja. -**[Opiskelijat](https://aka.ms/student-page)**, käyttääksesi tätä opetussuunnitelmaa, kloonaa koko repositorio omaan GitHub-tiliisi ja suorita tehtävät itseksesi tai ryhmässä: +**[Opiskelijat](https://aka.ms/student-page)**, tämän opintokokonaisuuden suorittamiseen, forkkaa koko repositorio omaan GitHub-tiliisi ja tee harjoitukset itseksesi tai ryhmässä: -- Aloita ennakkotentin tekemisellä. -- Lue luento ja tee aktiviteetit, pysähdy ja pohdi jokaisen tietokyselyn kohdalla. -- Yritä luoda projektit ymmärtämällä oppitunnit sen sijaan, että suoritat ratkaisukoodin; koodi on kuitenkin saatavilla kunkin projektipainotteisen oppitunnin `/solution`-kansiossa. -- Tee jälkitentti. +- Aloita esikurssivisailulla. +- Lue oppitunti ja tee tehtävät, pysähtyen ja pohtien jokaisen tietotarkistuksen kohdalla. +- Yritä luoda projektit ymmärtämällä oppitunti, älä pelkästään suorittamalla ratkaisukoodia; ratkaisukoodi on kuitenkin saatavilla kunkin projektilähtöisen oppitunnin `/solution`-kansiossa. +- Tee jälkikurssivisa. - Suorita haaste. - Tee tehtävä. -- Oppituntikokonaisuuden suorittamisen jälkeen käy [Keskustelupalstalla](https://github.com/microsoft/ML-For-Beginners/discussions) ja "opiskele ääneen" täyttämällä asianmukainen PAT-arviointi. PAT on edistymisarviointityökalu, jonka avulla voit edistää oppimistasi. Voit myös reagoida muiden PAT-arviointeihin, jotta voimme oppia yhdessä. +- Oppituntiryhmän suorittamisen jälkeen käy [Keskustelualueella](https://github.com/microsoft/ML-For-Beginners/discussions) ja "opiskele ääneen" täyttämällä sopiva PAT-arviointilomake. 'PAT' on etenemis-arviointityökalu, jonka avulla syvennät oppimistasi. Voit myös reagoida muiden PAT-arviointeihin, jotta voimme oppia yhdessä. -> Jatko-opiskeluun suosittelemme seuraamaan näitä [Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/k7o7tg1gp306q4?WT.mc_id=academic-77952-leestott) moduuleja ja oppimispolkuja. +> Jatko-opiskeluun suosittelemme näitä [Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/k7o7tg1gp306q4?WT.mc_id=academic-77952-leestott) -moduuleja ja oppimispolkuja. -**Opettajat**, olemme liittäneet [joitakin ehdotuksia](for-teachers.md) tämän opetussuunnitelman käyttämiseen. +**Opettajat**, olemme [lisänneet joitakin ehdotuksia](for-teachers.md) tähän opintokokonaisuuteen liittyen. --- -## Video-kävelyoppaat +## Videokierrokset -Jotkin oppitunnit ovat saatavilla lyhyinä videoina. Löydät ne kaikki oppitunneista tai Microsoft Developerin YouTube-kanavan [ML for Beginners -soittolistalta](https://aka.ms/ml-beginners-videos) klikkaamalla alla olevaa kuvaa. +Joitakin oppitunteja on saatavilla lyhyinä videoina. Löydät kaikki nämä oppitunneilla tai [ML for Beginners -soittolistalta Microsoft Developer YouTube -kanavalta](https://aka.ms/ml-beginners-videos) klikkaamalla alla olevaa kuvaa. -[![ML for beginners banner](../../../../translated_images/fi/ml-for-beginners-video-banner.63f694a100034bc6.webp)](https://aka.ms/ml-beginners-videos) +[![ML for beginners banner](../../translated_images/fi/ml-for-beginners-video-banner.63f694a100034bc6.webp)](https://aka.ms/ml-beginners-videos) --- -## Tapaa tiimi +## Tutustu tiimiin [![Promo video](../../images/ml.gif)](https://youtu.be/Tj1XWrDSYJU) @@ -106,71 +97,71 @@ Jotkin oppitunnit ovat saatavilla lyhyinä videoina. Löydät ne kaikki oppitunn ## Pedagogiikka -Olemme valinneet tämän opetussuunnitelman rakentamiseen kaksi pedagogista periaatetta: varmistaa, että se on käytännönläheinen **projektipohjainen** ja sisältää **tiheät tentit**. Lisäksi opetussuunnitelmalla on yhtenäinen **teema**, joka antaa sille johdonmukaisuuden. +Olemme valinneet tämän opintokokonaisuuden rakentamiseen kaksi pedagogista periaatetta: varmistaa, että se on käytännönläheinen **projektipohjainen** ja että siihen sisältyy **tiheästi visailuja**. Lisäksi tällä opintokokonaisuudella on yhteinen **teema**, joka antaa sille eheyttä. -Sisällön sovittaminen projekteihin tekee prosessista opiskelijoille mielekkäämmän ja käsitteiden omaksuminen paranee. Lisäksi matalan panoksen tentti ennen luentoa asettaa opiskelijan oppimistavoitteen aiheelle, ja jälkitentti varmistaa käsitteiden paremman omaksumisen. Tämä opetussuunnitelma on suunniteltu joustavaksi ja hauskaksi, ja se voidaan suorittaa kokonaan tai osittain. Projektit alkavat pieninä ja kasvavat monimutkaisemmiksi 12 viikon prosessin loppua kohti. Tämä opetussuunnitelma sisältää myös jälkikirjoituksen ML:n todellisista sovelluksista, jota voi käyttää lisäpisteenä tai keskustelun pohjana. +Sisällön kohdistaminen projekteihin tekee prosessista opiskelijoille kiinnostavamman ja konseptien muistamista tehostaa. Lisäksi pieni merkityksettömän tuntuinen valmistautumisvisailu ennen luentoa fokusoittaa opiskelijan asenteen aiheen oppimiseen, ja toinen jälkikäteen tehtävä visailu vahvistaa ja syventää oppimista. Tämä opintokokonaisuus on suunniteltu joustavaksi ja hauskaksi, ja se voidaan suorittaa kokonaan tai osittain. Projektit alkavat pienistä ja kasvavat monimutkaisemmaksi 12 viikon jakson aikana. Opintokokonaisuuteen sisältyy myös jälkikirjoitus koneoppimisen käytännön sovelluksista, jota voi käyttää lisäpisteisiin tai keskustelun pohjana. -> Löydät [käyttäytymissäännöstömme](CODE_OF_CONDUCT.md), [Osallistumisohjeet](CONTRIBUTING.md), [Käännösohjeet](TRANSLATIONS.md) ja [Vianmääritysohjeet](TROUBLESHOOTING.md). Otamme mielellämme vastaan rakentavaa palautettasi! +> Löydät ohjeistuksemme: [Ohjeistus](CODE_OF_CONDUCT.md), [Osallistuminen](CONTRIBUTING.md), [Käännökset](TRANSLATIONS.md) ja [Vianmääritys](TROUBLESHOOTING.md). Otamme mielellämme vastaan rakentavaa palautetta! ## Jokainen oppitunti sisältää -- valinnaisen luonnoksen -- valinnaisen lisävideon -- video-kävelyoppaan (vain osassa oppitunteja) -- [ennakko-oppitentin](https://ff-quizzes.netlify.app/en/ml/) -- kirjallisen oppitunnin +- valinnainen luonnosmuistio +- valinnainen tukivideo +- video-opastus (vain joissakin oppitunneissa) +- [ennakko-oppituntivisa](https://ff-quizzes.netlify.app/en/ml/) +- kirjallinen oppitunti - projektipohjaisissa oppitunneissa askel askeleelta ohjeet projektin rakentamiseen -- tietokyselyitä +- tietotarkistuksia - haasteen - lisälukemista - tehtävän -- [jälkikäteen tehtävän tentin](https://ff-quizzes.netlify.app/en/ml/) - -> **Huomio kielistä**: Nämä oppitunnit on kirjoitettu pääasiassa Pythonilla, mutta monia on myös saatavilla R-kielellä. R-oppitunnin suorittamiseksi siirry `/solution`-kansioon ja etsi R-oppitunteja. Niissä on .rmd-pääte, joka tarkoittaa **R Markdown** -tiedostoa, joka on yksinkertaisesti määritelty `koodilohkojen` (R:n tai muiden kielien) ja `YAML-otsikon` (joka ohjaa, miten muotoilla tulokset kuten PDF) yhdistämisenä `Markdown-dokumenttiin`. Näin se toimii esimerkillisenä kirjoituskehyksenä data-analytiikassa, koska sen avulla voit yhdistää koodisi, sen tuottaman tuloksen ja ajatuksesi kirjoittamalla ne Markdowniin. Lisäksi R Markdown -tiedostot voidaan renderöidä erilaisiin tulostusmuotoihin, kuten PDF, HTML tai Word. -> **Huomautus visailuista**: Kaikki visailut löytyvät kansiosta [Quiz App folder](../../quiz-app), yhteensä 52 visailua, joissa kussakin on kolme kysymystä. Ne on linkitetty oppitunteihin, mutta visailusovellusta voi ajaa paikallisesti; noudata `quiz-app` -kansion ohjeita sovelluksen paikalliseen ajamiseen tai Azureen siirtämiseen. - -| Oppitunnin numero | Aihe | Oppituntiryhmä | Oppimistavoitteet | Linkitetty oppitunti | Tekijä | -| :---------------: | :----------------------------------------------------------: | :------------------------------------------------: | ------------------------------------------------------------------------------------------------------------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------: | -| 01 | Johdatus koneoppimiseen | [Introduction](1-Introduction/README.md) | Opi koneoppimisen peruskäsitteet | [Oppitunti](1-Introduction/1-intro-to-ML/README.md) | Muhammad | -| 02 | Koneoppimisen historia | [Introduction](1-Introduction/README.md) | Opi tämän alan historia | [Oppitunti](1-Introduction/2-history-of-ML/README.md) | Jen ja Amy | -| 03 | Oikeudenmukaisuus ja koneoppiminen | [Introduction](1-Introduction/README.md) | Mitkä ovat tärkeät filosofiset kysymykset oikeudenmukaisuudesta, jotka opiskelijoiden tulisi huomioida rakentaessaan ja käyttäessään ML-malleja? | [Oppitunti](1-Introduction/3-fairness/README.md) | Tomomi | -| 04 | Koneoppimisen menetelmiä | [Introduction](1-Introduction/README.md) | Mitä menetelmiä ML-tutkijat käyttävät mallien rakentamiseen? | [Oppitunti](1-Introduction/4-techniques-of-ML/README.md) | Chris ja Jen | -| 05 | Johdatus regressioon | [Regression](2-Regression/README.md) | Aloita Pythonilla ja Scikit-learnillä regressiomalleihin | [Python](2-Regression/1-Tools/README.md) • [R](../../2-Regression/1-Tools/solution/R/lesson_1.html) | Jen • Eric Wanjau | -| 06 | Pohjoisamerikkalaiset kurpitsahinnat 🎃 | [Regression](2-Regression/README.md) | Visualisoi ja puhdista dataa koneoppimista varten | [Python](2-Regression/2-Data/README.md) • [R](../../2-Regression/2-Data/solution/R/lesson_2.html) | Jen • Eric Wanjau | -| 07 | Pohjoisamerikkalaiset kurpitsahinnat 🎃 | [Regression](2-Regression/README.md) | Rakenna lineaarinen ja polynominen regressiomalli | [Python](2-Regression/3-Linear/README.md) • [R](../../2-Regression/3-Linear/solution/R/lesson_3.html) | Jen ja Dmitry • Eric Wanjau | -| 08 | Pohjoisamerikkalaiset kurpitsahinnat 🎃 | [Regression](2-Regression/README.md) | Rakenna logistinen regressiomalli | [Python](2-Regression/4-Logistic/README.md) • [R](../../2-Regression/4-Logistic/solution/R/lesson_4.html) | Jen • Eric Wanjau | -| 09 | Web-sovellus 🔌 | [Web App](3-Web-App/README.md) | Rakenna web-sovellus koulutetun mallisi käyttöön | [Python](3-Web-App/1-Web-App/README.md) | Jen | -| 10 | Johdatus luokitteluun | [Classification](4-Classification/README.md) | Puhdista, valmistele ja visualisoi data; johdatus luokitteluun | [Python](4-Classification/1-Introduction/README.md) • [R](../../4-Classification/1-Introduction/solution/R/lesson_10.html) | Jen ja Cassie • Eric Wanjau | -| 11 | Herkulliset aasialaiset ja intialaiset ruoat 🍜 | [Classification](4-Classification/README.md) | Johdatus luokittelijoihin | [Python](4-Classification/2-Classifiers-1/README.md) • [R](../../4-Classification/2-Classifiers-1/solution/R/lesson_11.html) | Jen ja Cassie • Eric Wanjau | -| 12 | Herkulliset aasialaiset ja intialaiset ruoat 🍜 | [Classification](4-Classification/README.md) | Lisää luokittelijoita | [Python](4-Classification/3-Classifiers-2/README.md) • [R](../../4-Classification/3-Classifiers-2/solution/R/lesson_12.html) | Jen ja Cassie • Eric Wanjau | -| 13 | Herkulliset aasialaiset ja intialaiset ruoat 🍜 | [Classification](4-Classification/README.md) | Rakenna suosittelujärjestelmän web-sovellus mallisi avulla | [Python](4-Classification/4-Applied/README.md) | Jen | -| 14 | Johdatus klusterointiin | [Clustering](5-Clustering/README.md) | Puhdista, valmistele ja visualisoi datasi; Johdatus klusterointiin | [Python](5-Clustering/1-Visualize/README.md) • [R](../../5-Clustering/1-Visualize/solution/R/lesson_14.html) | Jen • Eric Wanjau | -| 15 | Nigerialaisen musiikkimaun tutkimista 🎧 | [Clustering](5-Clustering/README.md) | Tutustu K-Means-klusterointimenetelmään | [Python](5-Clustering/2-K-Means/README.md) • [R](../../5-Clustering/2-K-Means/solution/R/lesson_15.html) | Jen • Eric Wanjau | -| 16 | Johdatus luonnollisen kielen käsittelyyn ☕️ | [Natural language processing](6-NLP/README.md) | Opi NLP:n perusteet rakentamalla yksinkertainen botti | [Python](6-NLP/1-Introduction-to-NLP/README.md) | Stephen | -| 17 | Yleisiä NLP-tehtäviä ☕️ | [Natural language processing](6-NLP/README.md) | Syvennä NLP-tietoasi ymmärtämällä yleisiä kielirakenteissa tarvittavia tehtäviä | [Python](6-NLP/2-Tasks/README.md) | Stephen | -| 18 | Käännös ja tunteiden analysointi ♥️ | [Natural language processing](6-NLP/README.md) | Käännös ja tunteiden analysointi Jane Austenin kanssa | [Python](6-NLP/3-Translation-Sentiment/README.md) | Stephen | -| 19 | Euroopan romanttiset hotellit ♥️ | [Natural language processing](6-NLP/README.md) | Tunteiden analysointi hotelliarvioiden 1 avulla | [Python](6-NLP/4-Hotel-Reviews-1/README.md) | Stephen | -| 20 | Euroopan romanttiset hotellit ♥️ | [Natural language processing](6-NLP/README.md) | Tunteiden analysointi hotelliarvioiden 2 avulla | [Python](6-NLP/5-Hotel-Reviews-2/README.md) | Stephen | -| 21 | Johdatus aikasarjaennusteisiin | [Time series](7-TimeSeries/README.md) | Johdatus aikasarjaennusteisiin | [Python](7-TimeSeries/1-Introduction/README.md) | Francesca | -| 22 | ⚡️ Maailman sähkönkulutus ⚡️ - aikasarjaennuste ARIMA:lla | [Time series](7-TimeSeries/README.md) | Aikasarjaennuste ARIMA-mallilla | [Python](7-TimeSeries/2-ARIMA/README.md) | Francesca | -| 23 | ⚡️ Maailman sähkönkulutus ⚡️ - aikasarjaennuste SVR:llä | [Time series](7-TimeSeries/README.md) | Aikasarjaennuste tukivektoriregressiolla | [Python](7-TimeSeries/3-SVR/README.md) | Anirban | -| 24 | Johdatus vahvistusoppimiseen | [Reinforcement learning](8-Reinforcement/README.md) | Johdatus vahvistusoppimiseen Q-Learningin avulla | [Python](8-Reinforcement/1-QLearning/README.md) | Dmitry | -| 25 | Auta Peteriä välttelemään sutta! 🐺 | [Reinforcement learning](8-Reinforcement/README.md) | Vahvistusoppiminen Gymissä | [Python](8-Reinforcement/2-Gym/README.md) | Dmitry | -| Jälkikirjoitus | Käytännön ML-tilanteita ja sovelluksia | [ML in the Wild](9-Real-World/README.md) | Mielenkiintoisia ja paljastavia käytännön esimerkkejä perinteisestä ML:stä | [Oppitunti](9-Real-World/1-Applications/README.md) | Tiimi | -| Jälkikirjoitus | Mallin virheenkorjaus ML:ssä RAI-kojelautaa käyttäen | [ML in the Wild](9-Real-World/README.md) | Mallin virheenkorjaus koneoppimisessa Responsible AI -kojelauta-komponenttien avulla | [Oppitunti](9-Real-World/2-Debugging-ML-Models/README.md) | Ruth Yakubu | +- [jälki-oppituntivisa](https://ff-quizzes.netlify.app/en/ml/) + +> **Huomautus kielistä**: Nämä oppitunnit on pääosin kirjoitettu Pythonilla, mutta monet ovat saatavilla myös R-kielellä. R-oppitunnin suorittamiseksi mene `/solution`-kansioon ja etsi R-opetuksia. Niissä on .rmd-pääte, joka tarkoittaa **R Markdown** -tiedostoa, joka on yksinkertaistettuna `koodilohkojen` (R:n tai muiden kielten) ja `YAML-otsikon` (joka ohjaa vientimuotojen, kuten PDF:n muodostamista) upotusta `Markdown`-asiakirjassa. Tämä toimii erinomaisena julkaisualustana data scienceen, koska voit yhdistää koodisi, sen tuotoksen ja ajatuksesi kirjoittamalla ne Markdown-muotoon. Lisäksi R Markdown -asiakirjat voidaan muuntaa eri vientimuodoiksi, kuten PDF, HTML tai Word. +> **Muistutus visailuista**: Kaikki visailut löytyvät [Quiz App -kansiosta](../../quiz-app), yhteensä 52 visailua, joissa kukin sisältää kolme kysymystä. Ne on linkitetty oppituntien sisällä, mutta visailusovellusta voi käyttää myös paikallisesti; noudata `quiz-app`-kansion ohjeita paikalliseen isännöintiin tai käyttöönottoon Azureen. + +| Oppitunnin numero | Aihe | Oppituntujen ryhmittely | Oppimistavoitteet | Linkitetty oppitunti | Tekijä | +| :---------------: | :----------------------------------------------------------: | :----------------------------------------------------------: | ------------------------------------------------------------------------------------------------------------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------: | :-------------------------------------------------: | +| 01 | Johdanto koneoppimiseen | [Johdanto](1-Introduction/README.md) | Opi koneoppimisen peruskäsitteet | [Oppitunti](1-Introduction/1-intro-to-ML/README.md) | Muhammad | +| 02 | Koneoppimisen historia | [Johdanto](1-Introduction/README.md) | Opi alan taustasta | [Oppitunti](1-Introduction/2-history-of-ML/README.md) | Jen ja Amy | +| 03 | Oikeudenmukaisuus ja koneoppiminen | [Johdanto](1-Introduction/README.md) | Mitkä ovat tärkeimmät oikeudenmukaisuuteen liittyvät filosofiset kysymykset, jotka oppilaiden tulisi huomioida koneoppimismalleja rakentaessa ja käyttäessä? | [Oppitunti](1-Introduction/3-fairness/README.md) | Tomomi | +| 04 | Tekniikat koneoppimisessa | [Johdanto](1-Introduction/README.md) | Mitä tekniikoita koneoppimisen tutkijat käyttävät mallien rakentamisessa? | [Oppitunti](1-Introduction/4-techniques-of-ML/README.md) | Chris ja Jen | +| 05 | Johdanto regressioon | [Regressio](2-Regression/README.md) | Pääset alkuun Pythonilla ja Scikit-learnillä regressiomallien kanssa | [Python](2-Regression/1-Tools/README.md) • [R](../../2-Regression/1-Tools/solution/R/lesson_1.html) | Jen • Eric Wanjau | +| 06 | Pohjois-Amerikan kurpitsahinnat 🎃 | [Regressio](2-Regression/README.md) | Visualisoi ja puhdista data koneoppimisen valmistelussa | [Python](2-Regression/2-Data/README.md) • [R](../../2-Regression/2-Data/solution/R/lesson_2.html) | Jen • Eric Wanjau | +| 07 | Pohjois-Amerikan kurpitsahinnat 🎃 | [Regressio](2-Regression/README.md) | Rakenna lineaarisia ja polynomisia regressiomalleja | [Python](2-Regression/3-Linear/README.md) • [R](../../2-Regression/3-Linear/solution/R/lesson_3.html) | Jen ja Dmitry • Eric Wanjau | +| 08 | Pohjois-Amerikan kurpitsahinnat 🎃 | [Regressio](2-Regression/README.md) | Rakenna logistisen regression malli | [Python](2-Regression/4-Logistic/README.md) • [R](../../2-Regression/4-Logistic/solution/R/lesson_4.html) | Jen • Eric Wanjau | +| 09 | Verkkosovellus 🔌 | [Verkkosovellus](3-Web-App/README.md) | Rakenna verkkosovellus käyttämään valmennettua malliasi | [Python](3-Web-App/1-Web-App/README.md) | Jen | +| 10 | Johdanto luokitteluun | [Luokittelu](4-Classification/README.md) | Puhdista, valmistele ja visualisoi datasi; johdanto luokitteluun | [Python](4-Classification/1-Introduction/README.md) • [R](../../4-Classification/1-Introduction/solution/R/lesson_10.html) | Jen ja Cassie • Eric Wanjau | +| 11 | Herkulliset aasialaiset ja intialaiset ruoat 🍜 | [Luokittelu](4-Classification/README.md) | Johdanto luokittelijoihin | [Python](4-Classification/2-Classifiers-1/README.md) • [R](../../4-Classification/2-Classifiers-1/solution/R/lesson_11.html) | Jen ja Cassie • Eric Wanjau | +| 12 | Herkulliset aasialaiset ja intialaiset ruoat 🍜 | [Luokittelu](4-Classification/README.md) | Lisää luokittelijoita | [Python](4-Classification/3-Classifiers-2/README.md) • [R](../../4-Classification/3-Classifiers-2/solution/R/lesson_12.html) | Jen ja Cassie • Eric Wanjau | +| 13 | Herkulliset aasialaiset ja intialaiset ruoat 🍜 | [Luokittelu](4-Classification/README.md) | Rakenna suositussovellus mallisi avulla | [Python](4-Classification/4-Applied/README.md) | Jen | +| 14 | Johdanto klusterointiin | [Klusterointi](5-Clustering/README.md) | Puhdista, valmistele ja visualisoi data; johdanto klusterointiin | [Python](5-Clustering/1-Visualize/README.md) • [R](../../5-Clustering/1-Visualize/solution/R/lesson_14.html) | Jen • Eric Wanjau | +| 15 | Nigeerialaisten musiikkimakujen tutkiminen 🎧 | [Klusterointi](5-Clustering/README.md) | Tutustu K-Means klusterointimenetelmään | [Python](5-Clustering/2-K-Means/README.md) • [R](../../5-Clustering/2-K-Means/solution/R/lesson_15.html) | Jen • Eric Wanjau | +| 16 | Johdanto luonnollisen kielen käsittelyyn ☕️ | [Luonnollisen kielen käsittely](6-NLP/README.md) | Opi NLP:n perusteet rakentamalla yksinkertainen botti | [Python](6-NLP/1-Introduction-to-NLP/README.md) | Stephen | +| 17 | Tavalliset NLP-tehtävät ☕️ | [Luonnollisen kielen käsittely](6-NLP/README.md) | Syvennä NLP-tietämystäsi ymmärtämällä yleisiä kielirakenteita koskevia tehtäviä | [Python](6-NLP/2-Tasks/README.md) | Stephen | +| 18 | Käännös ja tunneanalyysi ♥️ | [Luonnollisen kielen käsittely](6-NLP/README.md) | Käännös ja tunneanalyysi Jane Austenin tekstien avulla | [Python](6-NLP/3-Translation-Sentiment/README.md) | Stephen | +| 19 | Euroopan romanttiset hotellit ♥️ | [Luonnollisen kielen käsittely](6-NLP/README.md) | Tunneanalyysi hotelliarvosteluilla 1 | [Python](6-NLP/4-Hotel-Reviews-1/README.md) | Stephen | +| 20 | Euroopan romanttiset hotellit ♥️ | [Luonnollisen kielen käsittely](6-NLP/README.md) | Tunneanalyysi hotelliarvosteluilla 2 | [Python](6-NLP/5-Hotel-Reviews-2/README.md) | Stephen | +| 21 | Johdanto aikasarjaennusteisiin | [Aikasarjat](7-TimeSeries/README.md) | Johdanto aikasarjaennusteisiin | [Python](7-TimeSeries/1-Introduction/README.md) | Francesca | +| 22 | ⚡️ Maailman sähkönkulutus ⚡️ - aikasarjaennuste ARIMAllä | [Aikasarjat](7-TimeSeries/README.md) | Aikasarjaennuste ARIMA-mallilla | [Python](7-TimeSeries/2-ARIMA/README.md) | Francesca | +| 23 | ⚡️ Maailman sähkönkulutus ⚡️ - aikasarjaennuste SVR:llä | [Aikasarjat](7-TimeSeries/README.md) | Aikasarjaennuste tukevaa vektoriregressoria käyttäen | [Python](7-TimeSeries/3-SVR/README.md) | Anirban | +| 24 | Johdanto vahvistusoppimiseen | [Vahvistusoppiminen](8-Reinforcement/README.md) | Johdanto vahvistusoppimiseen käyttäen Q-Learningia | [Python](8-Reinforcement/1-QLearning/README.md) | Dmitry | +| 25 | Auta Peteriä välttämään susi! 🐺 | [Vahvistusoppiminen](8-Reinforcement/README.md) | Vahvistusoppimisen Gym | [Python](8-Reinforcement/2-Gym/README.md) | Dmitry | +| Jälkikirjoitus | Todelliset ML-skenaariot ja sovellukset | [ML luonnossa](9-Real-World/README.md) | Mielenkiintoisia ja paljastavia käytännön sovelluksia klassiselle koneoppimiselle | [Oppitunti](9-Real-World/1-Applications/README.md) | Tiimi | +| Jälkikirjoitus | Mallien virheenkorjaus koneoppimisessa RAI-hallintapaneelilla | [ML luonnossa](9-Real-World/README.md) | Mallien virheenkorjaus koneoppimisessa käyttäen Responsible AI -hallintapaneelin komponentteja | [Oppitunti](9-Real-World/2-Debugging-ML-Models/README.md) | Ruth Yakubu | > [löydä kaikki tämän kurssin lisäresurssit Microsoft Learn -kokoelmastamme](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) ## Offline-käyttö -Voit käyttää tätä dokumentaatiota offline-tilassa käyttämällä [Docsify](https://docsify.js.org/#/). Tee fork tähän repositorioon, [asenna Docsify](https://docsify.js.org/#/quickstart) paikalliselle koneellesi, ja tämän repositorion juuressa kirjoita `docsify serve`. Verkkosivusto palvelee portissa 3000 paikallisella koneellasi: `localhost:3000`. +Voit käyttää tätä dokumentaatiota offline-tilassa käyttämällä [Docsify](https://docsify.js.org/#/). Forkkaa tämä repositorio, [asenna Docsify](https://docsify.js.org/#/quickstart) paikalliselle koneellesi ja sen jälkeen tämän repositorion juurikansiossa kirjoita `docsify serve`. Sivusto palvellaan portissa 3000 paikallisessa isäntäkoneessasi: `localhost:3000`. -## PDF:t +## PDF-tiedostot -Löydät opetussuunnitelman pdf-version linkkeineen [täältä](https://microsoft.github.io/ML-For-Beginners/pdf/readme.pdf). +Löydät opetussuunnitelman PDF-version linkkeineen [täältä](https://microsoft.github.io/ML-For-Beginners/pdf/readme.pdf). -## 🎒 Muut kurssit +## 🎒 Muut kurssit Tiimimme tuottaa myös muita kursseja! Tutustu: @@ -190,43 +181,43 @@ Tiimimme tuottaa myös muita kursseja! Tutustu: --- ### Generative AI Series -[![Generatiivinen tekoäly aloittelijoille](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) -[![Generatiivinen tekoäly (.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) -[![Generatiivinen tekoäly (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) -[![Generatiivinen tekoäly (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) +[![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) --- - -### Perusopetus -[![ML aloittelijoille](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) -[![Datatiede aloittelijoille](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) -[![Tekoäly aloittelijoille](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) -[![Kyberturvallisuus aloittelijoille](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-kehitys aloittelijoille](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 aloittelijoille](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-kehitys aloittelijoille](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) + +### Perusoppiminen +[![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) --- - + ### Copilot-sarja -[![Copilot tekoälyn pariohjelmointiin](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 C#/.NET:lle](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-seikkailu](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) -## Apua saamassa +## Hanki apua -Jos jäät jumiin tai sinulla on kysyttävää tekoälysovellusten rakentamisesta, liity muiden oppijoiden ja kokeneiden kehittäjien keskusteluihin MCP:stä. Se on kannustava yhteisö, jossa kysymykset ovat tervetulleita ja tieto jaetaan vapaaehtoisesti. +Jos jumitut tai sinulla on kysymyksiä AI-sovellusten rakentamisesta. Liity muiden oppijoiden ja kokeneiden kehittäjien keskusteluihin MCP:stä. Se on kannustava yhteisö, jossa kysymykset ovat tervetulleita ja tieto jaetaan vapaasti. [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -Jos sinulla on tuotepalaute tai kohtaat virheitä rakennusvaiheessa, vieraile: +Jos sinulla on tuotepalautetta tai virheitä rakentamisen aikana, vieraile: [![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) --- -**Vastuuvapauslauseke**: -Tämä asiakirja on käännetty käyttäen tekoälypohjaista käännöspalvelua [Co-op Translator](https://github.com/Azure/co-op-translator). Vaikka pyrimme tarkkuuteen, otathan huomioon, että automaattikäännöksissä saattaa esiintyä virheitä tai epätarkkuuksia. Alkuperäinen asiakirja omalla kielellään on virallinen ja auktoriteettinen lähde. Kriittisissä tiedoissa suosittelemme ammattimaisen ihmiskääntäjän käyttöä. Emme ole vastuussa mahdollisista väärinymmärryksistä tai tulkinnoista, jotka johtuvat tämän käännöksen käytöstä. +**Vastuuvapauslauseke**: +Tämä asiakirja on käännetty tekoälypohjaisella käännöspalvelulla [Co-op Translator](https://github.com/Azure/co-op-translator). Vaikka pyrimme tarkkuuteen, huomioithan, että automaattiset käännökset saattavat sisältää virheitä tai epätarkkuuksia. Alkuperäinen asiakirja sen alkuperäisellä kielellä on pääteltäväksi viralliseksi lähteeksi. Tärkeiden tietojen kohdalla suositellaan ammattimaista ihmiskäännöstä. Emme ole vastuussa tämän käännöksen käytöstä johtuvista väärinymmärryksistä tai tulkinnoista. \ No newline at end of file diff --git a/translations/fi/SECURITY.md b/translations/fi/SECURITY.md index b86bc02b3..67f714bc5 100644 --- a/translations/fi/SECURITY.md +++ b/translations/fi/SECURITY.md @@ -1,12 +1,3 @@ - ## Turvallisuus Microsoft suhtautuu vakavasti ohjelmistotuotteidensa ja palveluidensa turvallisuuteen, mukaan lukien kaikki lähdekoodivarastot, joita hallinnoidaan GitHub-organisaatioidemme kautta, kuten [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) ja [GitHub-organisaatiomme](https://opensource.microsoft.com/). diff --git a/translations/fi/SUPPORT.md b/translations/fi/SUPPORT.md index 92f0eef62..baf2343a1 100644 --- a/translations/fi/SUPPORT.md +++ b/translations/fi/SUPPORT.md @@ -1,12 +1,3 @@ - # Tuki ## Kuinka raportoida ongelmia ja saada apua diff --git a/translations/fi/TROUBLESHOOTING.md b/translations/fi/TROUBLESHOOTING.md index 01fcb9b03..76710dc56 100644 --- a/translations/fi/TROUBLESHOOTING.md +++ b/translations/fi/TROUBLESHOOTING.md @@ -1,12 +1,3 @@ - # Vianmääritysopas Tämä opas auttaa ratkaisemaan yleisiä ongelmia Machine Learning for Beginners -opetussuunnitelman parissa. Jos et löydä ratkaisua täältä, tarkista [Discord-keskustelut](https://aka.ms/foundry/discord) tai [avaa ongelma](https://github.com/microsoft/ML-For-Beginners/issues). diff --git a/translations/fi/docs/_sidebar.md b/translations/fi/docs/_sidebar.md index e1e1005e7..4324b165d 100644 --- a/translations/fi/docs/_sidebar.md +++ b/translations/fi/docs/_sidebar.md @@ -1,12 +1,3 @@ - - Johdanto - [Johdatus koneoppimiseen](../1-Introduction/1-intro-to-ML/README.md) - [Koneoppimisen historia](../1-Introduction/2-history-of-ML/README.md) diff --git a/translations/fi/for-teachers.md b/translations/fi/for-teachers.md index 375137ba2..7525ec3c4 100644 --- a/translations/fi/for-teachers.md +++ b/translations/fi/for-teachers.md @@ -1,12 +1,3 @@ - ## Opettajille Haluaisitko käyttää tätä opetusohjelmaa luokassasi? Ole hyvä ja käytä vapaasti! diff --git a/translations/fi/quiz-app/README.md b/translations/fi/quiz-app/README.md index 226419624..4c101769b 100644 --- a/translations/fi/quiz-app/README.md +++ b/translations/fi/quiz-app/README.md @@ -1,12 +1,3 @@ - # Visailut Nämä visailut ovat ML-kurssin ennakko- ja jälkiluennon visailuja osoitteessa https://aka.ms/ml-beginners diff --git a/translations/fi/sketchnotes/LICENSE.md b/translations/fi/sketchnotes/LICENSE.md index 96c51752b..fe9fbde06 100644 --- a/translations/fi/sketchnotes/LICENSE.md +++ b/translations/fi/sketchnotes/LICENSE.md @@ -1,12 +1,3 @@ - Oikeudet, tämä Public License koskee myös sitä tietokantaa; ja c. et voi tarjota tai asettaa lisäehtoja tai -rajoituksia, tai soveltaa mitään Tehokkaita Teknologisia Toimenpiteitä, jotka rajoittavat oikeuksien käyttöä, jotka on myönnetty tämän Public License -lisenssin nojalla. diff --git a/translations/fi/sketchnotes/README.md b/translations/fi/sketchnotes/README.md index ab07e02dc..988e07238 100644 --- a/translations/fi/sketchnotes/README.md +++ b/translations/fi/sketchnotes/README.md @@ -1,12 +1,3 @@ - Kaikki opetusohjelman sketchnotet voi ladata täältä. 🖨 Tulostusta varten korkearesoluutioiset TIFF-versiot ovat saatavilla tässä repossa: [this repo](https://github.com/girliemac/a-picture-is-worth-a-1000-words/tree/main/ml/tiff). diff --git a/translations/no/.co-op-translator.json b/translations/no/.co-op-translator.json new file mode 100644 index 000000000..4f915eb4e --- /dev/null +++ b/translations/no/.co-op-translator.json @@ -0,0 +1,596 @@ +{ + "1-Introduction/1-intro-to-ML/README.md": { + "original_hash": "69389392fa6346e0dfa30f664b7b6fec", + "translation_date": "2025-09-05T21:43:11+00:00", + "source_file": "1-Introduction/1-intro-to-ML/README.md", + "language_code": "no" + }, + "1-Introduction/1-intro-to-ML/assignment.md": { + "original_hash": "4c4698044bb8af52cfb6388a4ee0e53b", + "translation_date": "2025-09-05T21:43:45+00:00", + "source_file": 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"a88d5918c1b9da69a40d917a0840c497", + "translation_date": "2025-09-05T21:56:51+00:00", + "source_file": "sketchnotes/README.md", + "language_code": "no" + } +} \ No newline at end of file diff --git a/translations/no/1-Introduction/1-intro-to-ML/README.md b/translations/no/1-Introduction/1-intro-to-ML/README.md index 818314455..e881074d8 100644 --- a/translations/no/1-Introduction/1-intro-to-ML/README.md +++ b/translations/no/1-Introduction/1-intro-to-ML/README.md @@ -1,12 +1,3 @@ - # Introduksjon til maskinlæring ## [Quiz før forelesning](https://ff-quizzes.netlify.app/en/ml/) diff --git a/translations/no/1-Introduction/1-intro-to-ML/assignment.md b/translations/no/1-Introduction/1-intro-to-ML/assignment.md index df81bae7d..987b2cedb 100644 --- a/translations/no/1-Introduction/1-intro-to-ML/assignment.md +++ b/translations/no/1-Introduction/1-intro-to-ML/assignment.md @@ -1,12 +1,3 @@ - # Kom i gang ## Instruksjoner diff --git a/translations/no/1-Introduction/2-history-of-ML/README.md b/translations/no/1-Introduction/2-history-of-ML/README.md index 8c47c5c39..210a8b6c9 100644 --- a/translations/no/1-Introduction/2-history-of-ML/README.md +++ b/translations/no/1-Introduction/2-history-of-ML/README.md @@ -1,12 +1,3 @@ - # Historien om maskinlæring ![Oppsummering av historien om maskinlæring i en sketchnote](../../../../sketchnotes/ml-history.png) diff --git a/translations/no/1-Introduction/2-history-of-ML/assignment.md b/translations/no/1-Introduction/2-history-of-ML/assignment.md index 47d322edc..f641019fe 100644 --- a/translations/no/1-Introduction/2-history-of-ML/assignment.md +++ b/translations/no/1-Introduction/2-history-of-ML/assignment.md @@ -1,12 +1,3 @@ - # Lag en tidslinje ## Instruksjoner diff --git a/translations/no/1-Introduction/3-fairness/README.md b/translations/no/1-Introduction/3-fairness/README.md index 5ca3fd6c8..44590cef4 100644 --- a/translations/no/1-Introduction/3-fairness/README.md +++ b/translations/no/1-Introduction/3-fairness/README.md @@ -1,12 +1,3 @@ - # Bygge maskinlæringsløsninger med ansvarlig AI ![Oppsummering av ansvarlig AI i maskinlæring i en sketchnote](../../../../sketchnotes/ml-fairness.png) diff --git a/translations/no/1-Introduction/3-fairness/assignment.md b/translations/no/1-Introduction/3-fairness/assignment.md index 665e36e24..1be2c34f0 100644 --- a/translations/no/1-Introduction/3-fairness/assignment.md +++ b/translations/no/1-Introduction/3-fairness/assignment.md @@ -1,12 +1,3 @@ - # Utforsk Responsible AI Toolbox ## Instruksjoner diff --git a/translations/no/1-Introduction/4-techniques-of-ML/README.md b/translations/no/1-Introduction/4-techniques-of-ML/README.md index bd864d844..c91be7fdb 100644 --- a/translations/no/1-Introduction/4-techniques-of-ML/README.md +++ b/translations/no/1-Introduction/4-techniques-of-ML/README.md @@ -1,12 +1,3 @@ - # Teknikker for maskinlæring Prosessen med å bygge, bruke og vedlikeholde maskinlæringsmodeller og dataene de bruker, er svært forskjellig fra mange andre utviklingsarbeidsflyter. I denne leksjonen vil vi avmystifisere prosessen og skissere de viktigste teknikkene du trenger å kjenne til. Du vil: diff --git a/translations/no/1-Introduction/4-techniques-of-ML/assignment.md b/translations/no/1-Introduction/4-techniques-of-ML/assignment.md index 37a3fb9fe..fe2cec84a 100644 --- a/translations/no/1-Introduction/4-techniques-of-ML/assignment.md +++ b/translations/no/1-Introduction/4-techniques-of-ML/assignment.md @@ -1,12 +1,3 @@ - # Intervju en data scientist ## Instruksjoner diff --git a/translations/no/1-Introduction/README.md b/translations/no/1-Introduction/README.md index b1f69c1d5..04863026a 100644 --- a/translations/no/1-Introduction/README.md +++ b/translations/no/1-Introduction/README.md @@ -1,12 +1,3 @@ - # Introduksjon til maskinlæring I denne delen av læreplanen vil du bli introdusert til de grunnleggende konseptene som ligger til grunn for feltet maskinlæring, hva det er, og lære om historien og teknikkene forskere bruker for å arbeide med det. La oss utforske denne nye verdenen av ML sammen! diff --git a/translations/no/2-Regression/1-Tools/README.md b/translations/no/2-Regression/1-Tools/README.md index f5c549de4..3723aa741 100644 --- a/translations/no/2-Regression/1-Tools/README.md +++ b/translations/no/2-Regression/1-Tools/README.md @@ -1,12 +1,3 @@ - # Kom i gang med Python og Scikit-learn for regresjonsmodeller ![Oppsummering av regresjoner i en sketchnote](../../../../sketchnotes/ml-regression.png) diff --git a/translations/no/2-Regression/1-Tools/assignment.md b/translations/no/2-Regression/1-Tools/assignment.md index 6920e8852..b413863c3 100644 --- a/translations/no/2-Regression/1-Tools/assignment.md +++ b/translations/no/2-Regression/1-Tools/assignment.md @@ -1,12 +1,3 @@ - # Regressjon med Scikit-learn ## Instruksjoner diff --git a/translations/no/2-Regression/1-Tools/solution/Julia/README.md b/translations/no/2-Regression/1-Tools/solution/Julia/README.md index f306208e7..83657dee9 100644 --- a/translations/no/2-Regression/1-Tools/solution/Julia/README.md +++ b/translations/no/2-Regression/1-Tools/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/2-Regression/2-Data/README.md b/translations/no/2-Regression/2-Data/README.md index 4e9f9688a..4a9e96129 100644 --- a/translations/no/2-Regression/2-Data/README.md +++ b/translations/no/2-Regression/2-Data/README.md @@ -1,12 +1,3 @@ - # Bygg en regresjonsmodell med Scikit-learn: forbered og visualiser data ![Infografikk for datavisualisering](../../../../2-Regression/2-Data/images/data-visualization.png) diff --git a/translations/no/2-Regression/2-Data/assignment.md b/translations/no/2-Regression/2-Data/assignment.md index c0fed87c9..f5ba1602d 100644 --- a/translations/no/2-Regression/2-Data/assignment.md +++ b/translations/no/2-Regression/2-Data/assignment.md @@ -1,12 +1,3 @@ - # Utforske Visualiseringer Det finnes flere forskjellige biblioteker tilgjengelige for datavisualisering. Lag noen visualiseringer ved hjelp av Gresskar-dataene i denne leksjonen med matplotlib og seaborn i en eksempel-notatbok. Hvilke biblioteker er enklest å jobbe med? diff --git a/translations/no/2-Regression/2-Data/solution/Julia/README.md b/translations/no/2-Regression/2-Data/solution/Julia/README.md index b9abe3546..a15806da8 100644 --- a/translations/no/2-Regression/2-Data/solution/Julia/README.md +++ b/translations/no/2-Regression/2-Data/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/2-Regression/3-Linear/README.md b/translations/no/2-Regression/3-Linear/README.md index 7ad70c6e9..6110fc1fd 100644 --- a/translations/no/2-Regression/3-Linear/README.md +++ b/translations/no/2-Regression/3-Linear/README.md @@ -1,12 +1,3 @@ - # Bygg en regresjonsmodell med Scikit-learn: regresjon på fire måter ![Infografikk for lineær vs. polynomisk regresjon](../../../../2-Regression/3-Linear/images/linear-polynomial.png) @@ -114,11 +105,11 @@ Nå som du har en forståelse av matematikken bak lineær regresjon, la oss lage Fra forrige leksjon har du sannsynligvis sett at gjennomsnittsprisen for ulike måneder ser slik ut: -Gjennomsnittspris per måned +Gjennomsnittspris per måned Dette antyder at det bør være en viss korrelasjon, og vi kan prøve å trene en lineær regresjonsmodell for å forutsi forholdet mellom `Måned` og `Pris`, eller mellom `DagIÅret` og `Pris`. Her er spredningsdiagrammet som viser det sistnevnte forholdet: -Spredningsdiagram av pris vs. dag i året +Spredningsdiagram av pris vs. dag i året La oss se om det er en korrelasjon ved hjelp av `corr`-funksjonen: @@ -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) ``` -Spredningsdiagram av pris vs. dag i året +Spredningsdiagram av pris vs. dag i året Vår undersøkelse antyder at sorten har større effekt på den totale prisen enn selve salgsdatoen. Vi kan se dette med et stolpediagram: @@ -145,7 +136,7 @@ Vår undersøkelse antyder at sorten har større effekt på den totale prisen en new_pumpkins.groupby('Variety')['Price'].mean().plot(kind='bar') ``` -Stolpediagram av pris vs. sort +Stolpediagram av pris vs. sort La oss for øyeblikket fokusere kun på én gresskarsort, 'pie type', og se hvilken effekt datoen har på prisen: @@ -153,7 +144,7 @@ La oss for øyeblikket fokusere kun på én gresskarsort, 'pie type', og se hvil pie_pumpkins = new_pumpkins[new_pumpkins['Variety']=='PIE TYPE'] pie_pumpkins.plot.scatter('DayOfYear','Price') ``` -Spredningsdiagram av pris vs. dag i året +Spredningsdiagram av pris vs. dag i året Hvis vi nå beregner korrelasjonen mellom `Pris` og `DagIÅret` ved hjelp av `corr`-funksjonen, vil vi få noe som `-0.27` - noe som betyr at det gir mening å trene en prediktiv modell. @@ -227,7 +218,7 @@ plt.scatter(X_test,y_test) plt.plot(X_test,pred) ``` -Lineær regresjon +Lineær regresjon ## Polynomisk regresjon @@ -256,7 +247,7 @@ Ved å bruke `PolynomialFeatures(2)` betyr det at vi vil inkludere alle andregra Pipelines kan brukes på samme måte som det opprinnelige `LinearRegression`-objektet, dvs. vi kan `fit` pipelinen, og deretter bruke `predict` for å få prediksjonsresultatene. Her er grafen som viser testdataene og tilnærmingskurven: -Polynomisk regresjon +Polynomisk regresjon Ved å bruke polynomisk regresjon kan vi få litt lavere MSE og høyere determinasjon, men ikke betydelig. Vi må ta hensyn til andre funksjoner! @@ -274,7 +265,7 @@ I en ideell verden ønsker vi å kunne forutsi priser for ulike gresskarsorter v Her kan du se hvordan gjennomsnittsprisen avhenger av sort: -Gjennomsnittspris etter sort +Gjennomsnittspris etter sort For å ta sort i betraktning, må vi først konvertere den til numerisk form, eller **enkode** den. Det finnes flere måter vi kan gjøre dette på: diff --git a/translations/no/2-Regression/3-Linear/assignment.md b/translations/no/2-Regression/3-Linear/assignment.md index ae3f34641..c0129645a 100644 --- a/translations/no/2-Regression/3-Linear/assignment.md +++ b/translations/no/2-Regression/3-Linear/assignment.md @@ -1,12 +1,3 @@ - # Lag en regresjonsmodell ## Instruksjoner diff --git a/translations/no/2-Regression/3-Linear/solution/Julia/README.md b/translations/no/2-Regression/3-Linear/solution/Julia/README.md index 524a6cbf3..a15806da8 100644 --- a/translations/no/2-Regression/3-Linear/solution/Julia/README.md +++ b/translations/no/2-Regression/3-Linear/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/2-Regression/4-Logistic/README.md b/translations/no/2-Regression/4-Logistic/README.md index f2f075119..b9a6dd02d 100644 --- a/translations/no/2-Regression/4-Logistic/README.md +++ b/translations/no/2-Regression/4-Logistic/README.md @@ -1,12 +1,3 @@ - # Logistisk regresjon for å forutsi kategorier ![Infografikk om logistisk vs. lineær regresjon](../../../../2-Regression/4-Logistic/images/linear-vs-logistic.png) diff --git a/translations/no/2-Regression/4-Logistic/assignment.md b/translations/no/2-Regression/4-Logistic/assignment.md index ec954c29d..1a1662144 100644 --- a/translations/no/2-Regression/4-Logistic/assignment.md +++ b/translations/no/2-Regression/4-Logistic/assignment.md @@ -1,12 +1,3 @@ - # Prøve på nytt med regresjon ## Instruksjoner diff --git a/translations/no/2-Regression/4-Logistic/solution/Julia/README.md b/translations/no/2-Regression/4-Logistic/solution/Julia/README.md index d4727769f..83657dee9 100644 --- a/translations/no/2-Regression/4-Logistic/solution/Julia/README.md +++ b/translations/no/2-Regression/4-Logistic/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/2-Regression/README.md b/translations/no/2-Regression/README.md index 292a6245e..2621f1076 100644 --- a/translations/no/2-Regression/README.md +++ b/translations/no/2-Regression/README.md @@ -1,12 +1,3 @@ - # Regresjonsmodeller for maskinlæring ## Regionalt tema: Regresjonsmodeller for gresskarpriser i Nord-Amerika 🎃 diff --git a/translations/no/3-Web-App/1-Web-App/README.md b/translations/no/3-Web-App/1-Web-App/README.md index ca4a5b331..8eef26a4d 100644 --- a/translations/no/3-Web-App/1-Web-App/README.md +++ b/translations/no/3-Web-App/1-Web-App/README.md @@ -1,12 +1,3 @@ - # Bygg en webapplikasjon for å bruke en ML-modell I denne leksjonen skal du trene en ML-modell på et datasett som er helt utenomjordisk: _UFO-observasjoner fra det siste århundret_, hentet fra NUFORCs database. diff --git a/translations/no/3-Web-App/1-Web-App/assignment.md b/translations/no/3-Web-App/1-Web-App/assignment.md index 7bccb7fe8..8c7a709a9 100644 --- a/translations/no/3-Web-App/1-Web-App/assignment.md +++ b/translations/no/3-Web-App/1-Web-App/assignment.md @@ -1,12 +1,3 @@ - # Prøv en annen modell ## Instruksjoner diff --git a/translations/no/3-Web-App/README.md b/translations/no/3-Web-App/README.md index 93d32a75b..a8c3c1acd 100644 --- a/translations/no/3-Web-App/README.md +++ b/translations/no/3-Web-App/README.md @@ -1,12 +1,3 @@ - # Bygg en nettapp for å bruke din ML-modell I denne delen av læreplanen vil du bli introdusert til et praktisk ML-tema: hvordan du lagrer din Scikit-learn-modell som en fil som kan brukes til å gjøre prediksjoner i en nettapplikasjon. Når modellen er lagret, vil du lære hvordan du bruker den i en nettapp bygget med Flask. Du vil først lage en modell ved hjelp av data som handler om UFO-observasjoner! Deretter vil du bygge en nettapp som lar deg skrive inn et antall sekunder sammen med en breddegrad og en lengdegrad for å forutsi hvilket land som rapporterte å ha sett en UFO. diff --git a/translations/no/4-Classification/1-Introduction/README.md b/translations/no/4-Classification/1-Introduction/README.md index 175022823..3fab034ea 100644 --- a/translations/no/4-Classification/1-Introduction/README.md +++ b/translations/no/4-Classification/1-Introduction/README.md @@ -1,12 +1,3 @@ - # Introduksjon til klassifisering I disse fire leksjonene skal du utforske et grunnleggende fokusområde innen klassisk maskinlæring - _klassifisering_. Vi skal gå gjennom bruken av ulike klassifiseringsalgoritmer med et datasett om alle de fantastiske kjøkkenene i Asia og India. Håper du er sulten! diff --git a/translations/no/4-Classification/1-Introduction/assignment.md b/translations/no/4-Classification/1-Introduction/assignment.md index 5621f050f..d26429f8a 100644 --- a/translations/no/4-Classification/1-Introduction/assignment.md +++ b/translations/no/4-Classification/1-Introduction/assignment.md @@ -1,12 +1,3 @@ - # Utforsk klassifiseringsmetoder ## Instruksjoner diff --git a/translations/no/4-Classification/1-Introduction/solution/Julia/README.md b/translations/no/4-Classification/1-Introduction/solution/Julia/README.md index 7d4d9eb97..83657dee9 100644 --- a/translations/no/4-Classification/1-Introduction/solution/Julia/README.md +++ b/translations/no/4-Classification/1-Introduction/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/4-Classification/2-Classifiers-1/README.md b/translations/no/4-Classification/2-Classifiers-1/README.md index 4f7eb8140..1e2a8b4d2 100644 --- a/translations/no/4-Classification/2-Classifiers-1/README.md +++ b/translations/no/4-Classification/2-Classifiers-1/README.md @@ -1,12 +1,3 @@ - # Klassifisering av matretter 1 I denne leksjonen skal du bruke datasettet du lagret fra forrige leksjon, som inneholder balanserte og rene data om matretter. diff --git a/translations/no/4-Classification/2-Classifiers-1/assignment.md b/translations/no/4-Classification/2-Classifiers-1/assignment.md index 0146f8081..22ca03279 100644 --- a/translations/no/4-Classification/2-Classifiers-1/assignment.md +++ b/translations/no/4-Classification/2-Classifiers-1/assignment.md @@ -1,12 +1,3 @@ - # Studer løserne ## Instruksjoner diff --git a/translations/no/4-Classification/2-Classifiers-1/solution/Julia/README.md b/translations/no/4-Classification/2-Classifiers-1/solution/Julia/README.md index 676b1899a..02b3c7e1b 100644 --- a/translations/no/4-Classification/2-Classifiers-1/solution/Julia/README.md +++ b/translations/no/4-Classification/2-Classifiers-1/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/4-Classification/3-Classifiers-2/README.md b/translations/no/4-Classification/3-Classifiers-2/README.md index 1597f23ef..af7054520 100644 --- a/translations/no/4-Classification/3-Classifiers-2/README.md +++ b/translations/no/4-Classification/3-Classifiers-2/README.md @@ -1,12 +1,3 @@ - # Klassifisering av matretter 2 I denne andre leksjonen om klassifisering vil du utforske flere måter å klassifisere numeriske data på. Du vil også lære om konsekvensene ved å velge én klassifikator fremfor en annen. diff --git a/translations/no/4-Classification/3-Classifiers-2/assignment.md b/translations/no/4-Classification/3-Classifiers-2/assignment.md index 3994d882b..b793e02c1 100644 --- a/translations/no/4-Classification/3-Classifiers-2/assignment.md +++ b/translations/no/4-Classification/3-Classifiers-2/assignment.md @@ -1,12 +1,3 @@ - # Parameterlek ## Instruksjoner diff --git a/translations/no/4-Classification/3-Classifiers-2/solution/Julia/README.md b/translations/no/4-Classification/3-Classifiers-2/solution/Julia/README.md index 7358749e8..a15806da8 100644 --- a/translations/no/4-Classification/3-Classifiers-2/solution/Julia/README.md +++ b/translations/no/4-Classification/3-Classifiers-2/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/4-Classification/4-Applied/README.md b/translations/no/4-Classification/4-Applied/README.md index 856f06f76..9ee147333 100644 --- a/translations/no/4-Classification/4-Applied/README.md +++ b/translations/no/4-Classification/4-Applied/README.md @@ -1,12 +1,3 @@ - # Bygg en webapp for matanbefalinger I denne leksjonen skal du bygge en klassifiseringsmodell ved hjelp av noen av teknikkene du har lært i tidligere leksjoner, samt det deilige matdatasettet som har blitt brukt gjennom denne serien. I tillegg skal du lage en liten webapp for å bruke en lagret modell, ved hjelp av Onnx sin web-runtime. diff --git a/translations/no/4-Classification/4-Applied/assignment.md b/translations/no/4-Classification/4-Applied/assignment.md index ee4994c01..9062e3908 100644 --- a/translations/no/4-Classification/4-Applied/assignment.md +++ b/translations/no/4-Classification/4-Applied/assignment.md @@ -1,12 +1,3 @@ - # Bygg en anbefalingsmotor ## Instruksjoner diff --git a/translations/no/4-Classification/README.md b/translations/no/4-Classification/README.md index b671e5e7d..f99e6b9b3 100644 --- a/translations/no/4-Classification/README.md +++ b/translations/no/4-Classification/README.md @@ -1,12 +1,3 @@ - # Komme i gang med klassifisering ## Regionalt tema: Deilige asiatiske og indiske retter 🍜 diff --git a/translations/no/5-Clustering/1-Visualize/README.md b/translations/no/5-Clustering/1-Visualize/README.md index 38e170865..061ab40f8 100644 --- a/translations/no/5-Clustering/1-Visualize/README.md +++ b/translations/no/5-Clustering/1-Visualize/README.md @@ -1,12 +1,3 @@ - # Introduksjon til klynging Klynging er en type [Usupervisert læring](https://wikipedia.org/wiki/Unsupervised_learning) som forutsetter at et datasett er umerket eller at dets input ikke er koblet til forhåndsdefinerte output. Det bruker ulike algoritmer for å sortere gjennom umerket data og gi grupperinger basert på mønstre det oppdager i dataen. diff --git a/translations/no/5-Clustering/1-Visualize/assignment.md b/translations/no/5-Clustering/1-Visualize/assignment.md index 6396a22d8..611578b6c 100644 --- a/translations/no/5-Clustering/1-Visualize/assignment.md +++ b/translations/no/5-Clustering/1-Visualize/assignment.md @@ -1,12 +1,3 @@ - # Utforsk andre visualiseringer for klynging ## Instruksjoner diff --git a/translations/no/5-Clustering/1-Visualize/solution/Julia/README.md b/translations/no/5-Clustering/1-Visualize/solution/Julia/README.md index 77649d6cb..83657dee9 100644 --- a/translations/no/5-Clustering/1-Visualize/solution/Julia/README.md +++ b/translations/no/5-Clustering/1-Visualize/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/5-Clustering/2-K-Means/README.md b/translations/no/5-Clustering/2-K-Means/README.md index 0afe2c2cb..8f44dd8f6 100644 --- a/translations/no/5-Clustering/2-K-Means/README.md +++ b/translations/no/5-Clustering/2-K-Means/README.md @@ -1,12 +1,3 @@ - # K-Means klynging ## [Pre-forelesningsquiz](https://ff-quizzes.netlify.app/en/ml/) diff --git a/translations/no/5-Clustering/2-K-Means/assignment.md b/translations/no/5-Clustering/2-K-Means/assignment.md index 2aed54d6f..bc14b55c5 100644 --- a/translations/no/5-Clustering/2-K-Means/assignment.md +++ b/translations/no/5-Clustering/2-K-Means/assignment.md @@ -1,12 +1,3 @@ - # Prøv forskjellige klyngemetoder ## Instruksjoner diff --git a/translations/no/5-Clustering/2-K-Means/solution/Julia/README.md b/translations/no/5-Clustering/2-K-Means/solution/Julia/README.md index 7f1044fe0..83657dee9 100644 --- a/translations/no/5-Clustering/2-K-Means/solution/Julia/README.md +++ b/translations/no/5-Clustering/2-K-Means/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/5-Clustering/README.md b/translations/no/5-Clustering/README.md index ef7101a03..ff92c93f5 100644 --- a/translations/no/5-Clustering/README.md +++ b/translations/no/5-Clustering/README.md @@ -1,12 +1,3 @@ - # Klusteringsmodeller for maskinlæring Klustering er en oppgave innen maskinlæring hvor man forsøker å finne objekter som ligner på hverandre og gruppere disse i grupper kalt klynger. Det som skiller klustering fra andre tilnærminger i maskinlæring, er at ting skjer automatisk. Faktisk kan man si at det er det motsatte av veiledet læring. diff --git a/translations/no/6-NLP/1-Introduction-to-NLP/README.md b/translations/no/6-NLP/1-Introduction-to-NLP/README.md index 1926b729d..32084e1f3 100644 --- a/translations/no/6-NLP/1-Introduction-to-NLP/README.md +++ b/translations/no/6-NLP/1-Introduction-to-NLP/README.md @@ -1,12 +1,3 @@ - # Introduksjon til naturlig språkbehandling Denne leksjonen dekker en kort historie og viktige konsepter innen *naturlig språkbehandling*, et underfelt av *datamaskinlingvistikk*. diff --git a/translations/no/6-NLP/1-Introduction-to-NLP/assignment.md b/translations/no/6-NLP/1-Introduction-to-NLP/assignment.md index 008e6d51a..81289ee10 100644 --- a/translations/no/6-NLP/1-Introduction-to-NLP/assignment.md +++ b/translations/no/6-NLP/1-Introduction-to-NLP/assignment.md @@ -1,12 +1,3 @@ - # Finn en bot ## Instruksjoner diff --git a/translations/no/6-NLP/2-Tasks/README.md b/translations/no/6-NLP/2-Tasks/README.md index 4a5092f37..54e1f0de7 100644 --- a/translations/no/6-NLP/2-Tasks/README.md +++ b/translations/no/6-NLP/2-Tasks/README.md @@ -1,12 +1,3 @@ - # Vanlige oppgaver og teknikker innen naturlig språkprosessering For de fleste oppgaver innen *naturlig språkprosessering* må teksten som skal behandles brytes ned, analyseres, og resultatene lagres eller kryssrefereres med regler og datasett. Disse oppgavene lar programmereren utlede _meningen_, _intensjonen_ eller bare _frekvensen_ av termer og ord i en tekst. diff --git a/translations/no/6-NLP/2-Tasks/assignment.md b/translations/no/6-NLP/2-Tasks/assignment.md index 6b2deeeee..f5b511ce6 100644 --- a/translations/no/6-NLP/2-Tasks/assignment.md +++ b/translations/no/6-NLP/2-Tasks/assignment.md @@ -1,12 +1,3 @@ - # Få en bot til å svare tilbake ## Instruksjoner diff --git a/translations/no/6-NLP/3-Translation-Sentiment/README.md b/translations/no/6-NLP/3-Translation-Sentiment/README.md index 3c675c3da..fbf19ff56 100644 --- a/translations/no/6-NLP/3-Translation-Sentiment/README.md +++ b/translations/no/6-NLP/3-Translation-Sentiment/README.md @@ -1,12 +1,3 @@ - # Oversettelse og sentimentanalyse med maskinlæring I de forrige leksjonene lærte du hvordan du bygger en enkel bot ved hjelp av `TextBlob`, et bibliotek som bruker maskinlæring i bakgrunnen for å utføre grunnleggende NLP-oppgaver som å trekke ut substantivfraser. En annen viktig utfordring innen datalingvistikk er nøyaktig _oversettelse_ av en setning fra ett muntlig eller skriftlig språk til et annet. diff --git a/translations/no/6-NLP/3-Translation-Sentiment/assignment.md b/translations/no/6-NLP/3-Translation-Sentiment/assignment.md index 3eac019db..94c77cdd7 100644 --- a/translations/no/6-NLP/3-Translation-Sentiment/assignment.md +++ b/translations/no/6-NLP/3-Translation-Sentiment/assignment.md @@ -1,12 +1,3 @@ - # Poetisk frihet ## Instruksjoner diff --git a/translations/no/6-NLP/3-Translation-Sentiment/solution/Julia/README.md b/translations/no/6-NLP/3-Translation-Sentiment/solution/Julia/README.md index fbf5f2b71..83657dee9 100644 --- a/translations/no/6-NLP/3-Translation-Sentiment/solution/Julia/README.md +++ b/translations/no/6-NLP/3-Translation-Sentiment/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/6-NLP/3-Translation-Sentiment/solution/R/README.md b/translations/no/6-NLP/3-Translation-Sentiment/solution/R/README.md index 172bd8e95..83657dee9 100644 --- a/translations/no/6-NLP/3-Translation-Sentiment/solution/R/README.md +++ b/translations/no/6-NLP/3-Translation-Sentiment/solution/R/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/6-NLP/4-Hotel-Reviews-1/README.md b/translations/no/6-NLP/4-Hotel-Reviews-1/README.md index 479001c08..37c670f02 100644 --- a/translations/no/6-NLP/4-Hotel-Reviews-1/README.md +++ b/translations/no/6-NLP/4-Hotel-Reviews-1/README.md @@ -1,12 +1,3 @@ - # Sentimentanalyse med hotellanmeldelser - bearbeiding av data I denne delen vil du bruke teknikkene fra de tidligere leksjonene til å utføre en utforskende dataanalyse av et stort datasett. Når du har fått en god forståelse av nytten av de ulike kolonnene, vil du lære: diff --git a/translations/no/6-NLP/4-Hotel-Reviews-1/assignment.md b/translations/no/6-NLP/4-Hotel-Reviews-1/assignment.md index 2f394cd90..8d3ee11dd 100644 --- a/translations/no/6-NLP/4-Hotel-Reviews-1/assignment.md +++ b/translations/no/6-NLP/4-Hotel-Reviews-1/assignment.md @@ -1,12 +1,3 @@ - # NLTK ## Instruksjoner diff --git a/translations/no/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md b/translations/no/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md index 5241e315f..02b3c7e1b 100644 --- a/translations/no/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md +++ b/translations/no/6-NLP/4-Hotel-Reviews-1/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/6-NLP/4-Hotel-Reviews-1/solution/R/README.md b/translations/no/6-NLP/4-Hotel-Reviews-1/solution/R/README.md index ad3cfa0ea..5c05143ea 100644 --- a/translations/no/6-NLP/4-Hotel-Reviews-1/solution/R/README.md +++ b/translations/no/6-NLP/4-Hotel-Reviews-1/solution/R/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/6-NLP/5-Hotel-Reviews-2/README.md b/translations/no/6-NLP/5-Hotel-Reviews-2/README.md index d35fa99aa..731849e87 100644 --- a/translations/no/6-NLP/5-Hotel-Reviews-2/README.md +++ b/translations/no/6-NLP/5-Hotel-Reviews-2/README.md @@ -1,12 +1,3 @@ - # Sentimentanalyse med hotellanmeldelser Nå som du har utforsket datasettet i detalj, er det på tide å filtrere kolonnene og deretter bruke NLP-teknikker på datasettet for å få nye innsikter om hotellene. diff --git a/translations/no/6-NLP/5-Hotel-Reviews-2/assignment.md b/translations/no/6-NLP/5-Hotel-Reviews-2/assignment.md index 3abc4945d..8c3fc2846 100644 --- a/translations/no/6-NLP/5-Hotel-Reviews-2/assignment.md +++ b/translations/no/6-NLP/5-Hotel-Reviews-2/assignment.md @@ -1,12 +1,3 @@ - # Prøv et annet datasett ## Instruksjoner diff --git a/translations/no/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md b/translations/no/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md index 6916ad447..338d1c642 100644 --- a/translations/no/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md +++ b/translations/no/6-NLP/5-Hotel-Reviews-2/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/6-NLP/5-Hotel-Reviews-2/solution/R/README.md b/translations/no/6-NLP/5-Hotel-Reviews-2/solution/R/README.md index a01c1cb11..83657dee9 100644 --- a/translations/no/6-NLP/5-Hotel-Reviews-2/solution/R/README.md +++ b/translations/no/6-NLP/5-Hotel-Reviews-2/solution/R/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/6-NLP/README.md b/translations/no/6-NLP/README.md index 018f279e6..31a1e08bc 100644 --- a/translations/no/6-NLP/README.md +++ b/translations/no/6-NLP/README.md @@ -1,12 +1,3 @@ - # Komme i gang med naturlig språkbehandling Naturlig språkbehandling (NLP) er evnen til et dataprogram til å forstå menneskelig språk slik det blir snakket og skrevet – referert til som naturlig språk. Det er en komponent av kunstig intelligens (AI). NLP har eksistert i mer enn 50 år og har røtter i lingvistikkens felt. Hele feltet er rettet mot å hjelpe maskiner med å forstå og behandle menneskelig språk. Dette kan deretter brukes til å utføre oppgaver som stavekontroll eller maskinoversettelse. Det har en rekke virkelige anvendelser innen flere felt, inkludert medisinsk forskning, søkemotorer og forretningsanalyse. diff --git a/translations/no/6-NLP/data/README.md b/translations/no/6-NLP/data/README.md index a778bfced..5c05143ea 100644 --- a/translations/no/6-NLP/data/README.md +++ b/translations/no/6-NLP/data/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/7-TimeSeries/1-Introduction/README.md b/translations/no/7-TimeSeries/1-Introduction/README.md index f9bbecdfb..8b246f48f 100644 --- a/translations/no/7-TimeSeries/1-Introduction/README.md +++ b/translations/no/7-TimeSeries/1-Introduction/README.md @@ -1,12 +1,3 @@ - # Introduksjon til tidsserieprognoser ![Oppsummering av tidsserier i en sketchnote](../../../../sketchnotes/ml-timeseries.png) diff --git a/translations/no/7-TimeSeries/1-Introduction/assignment.md b/translations/no/7-TimeSeries/1-Introduction/assignment.md index def0eccc0..5f9fb55e6 100644 --- a/translations/no/7-TimeSeries/1-Introduction/assignment.md +++ b/translations/no/7-TimeSeries/1-Introduction/assignment.md @@ -1,12 +1,3 @@ - # Visualiser noen flere tidsserier ## Instruksjoner diff --git a/translations/no/7-TimeSeries/1-Introduction/solution/Julia/README.md b/translations/no/7-TimeSeries/1-Introduction/solution/Julia/README.md index 0cb70787c..83657dee9 100644 --- a/translations/no/7-TimeSeries/1-Introduction/solution/Julia/README.md +++ b/translations/no/7-TimeSeries/1-Introduction/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/7-TimeSeries/1-Introduction/solution/R/README.md b/translations/no/7-TimeSeries/1-Introduction/solution/R/README.md index 6891f865b..83657dee9 100644 --- a/translations/no/7-TimeSeries/1-Introduction/solution/R/README.md +++ b/translations/no/7-TimeSeries/1-Introduction/solution/R/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/7-TimeSeries/2-ARIMA/README.md b/translations/no/7-TimeSeries/2-ARIMA/README.md index f84cddec5..906d3599f 100644 --- a/translations/no/7-TimeSeries/2-ARIMA/README.md +++ b/translations/no/7-TimeSeries/2-ARIMA/README.md @@ -1,12 +1,3 @@ - # Tidsserieprognoser med ARIMA I forrige leksjon lærte du litt om tidsserieprognoser og lastet inn et datasett som viser svingninger i elektrisk belastning over en tidsperiode. diff --git a/translations/no/7-TimeSeries/2-ARIMA/assignment.md b/translations/no/7-TimeSeries/2-ARIMA/assignment.md index 596fbd1a9..4c3614e54 100644 --- a/translations/no/7-TimeSeries/2-ARIMA/assignment.md +++ b/translations/no/7-TimeSeries/2-ARIMA/assignment.md @@ -1,12 +1,3 @@ - # En ny ARIMA-modell ## Instruksjoner diff --git a/translations/no/7-TimeSeries/2-ARIMA/solution/Julia/README.md b/translations/no/7-TimeSeries/2-ARIMA/solution/Julia/README.md index c9e9cafc5..83657dee9 100644 --- a/translations/no/7-TimeSeries/2-ARIMA/solution/Julia/README.md +++ b/translations/no/7-TimeSeries/2-ARIMA/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/7-TimeSeries/2-ARIMA/solution/R/README.md b/translations/no/7-TimeSeries/2-ARIMA/solution/R/README.md index 83cfabb17..83657dee9 100644 --- a/translations/no/7-TimeSeries/2-ARIMA/solution/R/README.md +++ b/translations/no/7-TimeSeries/2-ARIMA/solution/R/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/7-TimeSeries/3-SVR/README.md b/translations/no/7-TimeSeries/3-SVR/README.md index 196310431..fb63251f1 100644 --- a/translations/no/7-TimeSeries/3-SVR/README.md +++ b/translations/no/7-TimeSeries/3-SVR/README.md @@ -1,12 +1,3 @@ - # Tidsserieprognoser med Support Vector Regressor I forrige leksjon lærte du hvordan du bruker ARIMA-modellen til å lage tidsserieprediksjoner. Nå skal vi se på Support Vector Regressor-modellen, som er en regresjonsmodell brukt til å forutsi kontinuerlige data. diff --git a/translations/no/7-TimeSeries/3-SVR/assignment.md b/translations/no/7-TimeSeries/3-SVR/assignment.md index 31a6f9902..c844980ee 100644 --- a/translations/no/7-TimeSeries/3-SVR/assignment.md +++ b/translations/no/7-TimeSeries/3-SVR/assignment.md @@ -1,12 +1,3 @@ - # En ny SVR-modell ## Instruksjoner [^1] diff --git a/translations/no/7-TimeSeries/README.md b/translations/no/7-TimeSeries/README.md index 561496c7e..e020b4466 100644 --- a/translations/no/7-TimeSeries/README.md +++ b/translations/no/7-TimeSeries/README.md @@ -1,12 +1,3 @@ - # Introduksjon til tidsserieprognoser Hva er tidsserieprognoser? Det handler om å forutsi fremtidige hendelser ved å analysere trender fra fortiden. diff --git a/translations/no/8-Reinforcement/1-QLearning/README.md b/translations/no/8-Reinforcement/1-QLearning/README.md index 5b05f4c37..610d27242 100644 --- a/translations/no/8-Reinforcement/1-QLearning/README.md +++ b/translations/no/8-Reinforcement/1-QLearning/README.md @@ -1,12 +1,3 @@ - # Introduksjon til forsterkende læring og Q-Læring ![Oppsummering av forsterkning i maskinlæring i en sketchnote](../../../../sketchnotes/ml-reinforcement.png) diff --git a/translations/no/8-Reinforcement/1-QLearning/assignment.md b/translations/no/8-Reinforcement/1-QLearning/assignment.md index 4829c2457..53ac7ebda 100644 --- a/translations/no/8-Reinforcement/1-QLearning/assignment.md +++ b/translations/no/8-Reinforcement/1-QLearning/assignment.md @@ -1,12 +1,3 @@ - # En Mer Realistisk Verden I vår situasjon kunne Peter bevege seg rundt nesten uten å bli sliten eller sulten. I en mer realistisk verden må han sette seg ned og hvile fra tid til annen, og også spise for å holde seg i live. La oss gjøre vår verden mer realistisk ved å implementere følgende regler: diff --git a/translations/no/8-Reinforcement/1-QLearning/solution/Julia/README.md b/translations/no/8-Reinforcement/1-QLearning/solution/Julia/README.md index 817378398..5c05143ea 100644 --- a/translations/no/8-Reinforcement/1-QLearning/solution/Julia/README.md +++ b/translations/no/8-Reinforcement/1-QLearning/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/8-Reinforcement/1-QLearning/solution/R/README.md b/translations/no/8-Reinforcement/1-QLearning/solution/R/README.md index 9bc837dbc..5c05143ea 100644 --- a/translations/no/8-Reinforcement/1-QLearning/solution/R/README.md +++ b/translations/no/8-Reinforcement/1-QLearning/solution/R/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/8-Reinforcement/2-Gym/README.md b/translations/no/8-Reinforcement/2-Gym/README.md index 9e6c661bb..dacbb86de 100644 --- a/translations/no/8-Reinforcement/2-Gym/README.md +++ b/translations/no/8-Reinforcement/2-Gym/README.md @@ -1,12 +1,3 @@ - ## Forutsetninger I denne leksjonen skal vi bruke et bibliotek kalt **OpenAI Gym** for å simulere ulike **miljøer**. Du kan kjøre koden fra denne leksjonen lokalt (f.eks. fra Visual Studio Code), i så fall vil simuleringen åpne seg i et nytt vindu. Når du kjører koden online, kan det være nødvendig å gjøre noen justeringer i koden, som beskrevet [her](https://towardsdatascience.com/rendering-openai-gym-envs-on-binder-and-google-colab-536f99391cc7). diff --git a/translations/no/8-Reinforcement/2-Gym/assignment.md b/translations/no/8-Reinforcement/2-Gym/assignment.md index 7e77426d1..0011bd0d6 100644 --- a/translations/no/8-Reinforcement/2-Gym/assignment.md +++ b/translations/no/8-Reinforcement/2-Gym/assignment.md @@ -1,12 +1,3 @@ - # Tren Mountain Car [OpenAI Gym](http://gym.openai.com) er designet slik at alle miljøer tilbyr samme API - altså de samme metodene `reset`, `step` og `render`, og de samme abstraksjonene for **handlingsrom** og **observasjonsrom**. Derfor bør det være mulig å tilpasse de samme forsterkningslæringsalgoritmene til forskjellige miljøer med minimale kodeendringer. diff --git a/translations/no/8-Reinforcement/2-Gym/solution/Julia/README.md b/translations/no/8-Reinforcement/2-Gym/solution/Julia/README.md index b122e3ea1..02b3c7e1b 100644 --- a/translations/no/8-Reinforcement/2-Gym/solution/Julia/README.md +++ b/translations/no/8-Reinforcement/2-Gym/solution/Julia/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/8-Reinforcement/2-Gym/solution/R/README.md b/translations/no/8-Reinforcement/2-Gym/solution/R/README.md index c0a46e9ca..5c05143ea 100644 --- a/translations/no/8-Reinforcement/2-Gym/solution/R/README.md +++ b/translations/no/8-Reinforcement/2-Gym/solution/R/README.md @@ -1,12 +1,3 @@ - --- diff --git a/translations/no/8-Reinforcement/README.md b/translations/no/8-Reinforcement/README.md index cbc8660e7..3112b1ad8 100644 --- a/translations/no/8-Reinforcement/README.md +++ b/translations/no/8-Reinforcement/README.md @@ -1,12 +1,3 @@ - # Introduksjon til forsterkende læring Forsterkende læring, RL, regnes som en av de grunnleggende paradigmer innen maskinlæring, ved siden av veiledet læring og uveiledet læring. RL handler om beslutninger: å ta riktige beslutninger eller i det minste lære av dem. diff --git a/translations/no/9-Real-World/1-Applications/README.md b/translations/no/9-Real-World/1-Applications/README.md index 2a4fa00c4..09cb5aafa 100644 --- a/translations/no/9-Real-World/1-Applications/README.md +++ b/translations/no/9-Real-World/1-Applications/README.md @@ -1,12 +1,3 @@ - # Postscript: Maskinlæring i den virkelige verden ![Oppsummering av maskinlæring i den virkelige verden i en sketchnote](../../../../sketchnotes/ml-realworld.png) diff --git a/translations/no/9-Real-World/1-Applications/assignment.md b/translations/no/9-Real-World/1-Applications/assignment.md index dae422da1..b9b92dfaa 100644 --- a/translations/no/9-Real-World/1-Applications/assignment.md +++ b/translations/no/9-Real-World/1-Applications/assignment.md @@ -1,12 +1,3 @@ - # En ML Skattejakt ## Instruksjoner diff --git a/translations/no/9-Real-World/2-Debugging-ML-Models/README.md b/translations/no/9-Real-World/2-Debugging-ML-Models/README.md index 543d920dd..34765170e 100644 --- a/translations/no/9-Real-World/2-Debugging-ML-Models/README.md +++ b/translations/no/9-Real-World/2-Debugging-ML-Models/README.md @@ -1,12 +1,3 @@ - # Postscript: Modellfeilsøking i maskinlæring ved bruk av komponenter fra Responsible AI-dashboardet ## [Pre-lecture quiz](https://ff-quizzes.netlify.app/en/ml/) diff --git a/translations/no/9-Real-World/2-Debugging-ML-Models/assignment.md b/translations/no/9-Real-World/2-Debugging-ML-Models/assignment.md index 9fdb962a7..dae793e42 100644 --- a/translations/no/9-Real-World/2-Debugging-ML-Models/assignment.md +++ b/translations/no/9-Real-World/2-Debugging-ML-Models/assignment.md @@ -1,12 +1,3 @@ - # Utforsk Responsible AI (RAI) dashboard ## Instruksjoner diff --git a/translations/no/9-Real-World/README.md b/translations/no/9-Real-World/README.md index ad21dc55a..acb698c16 100644 --- a/translations/no/9-Real-World/README.md +++ b/translations/no/9-Real-World/README.md @@ -1,12 +1,3 @@ - # Postscript: Virkelige anvendelser av klassisk maskinlæring I denne delen av læreplanen vil du bli introdusert for noen virkelige anvendelser av klassisk ML. Vi har søkt på internett for å finne forskningsartikler og artikler om applikasjoner som har brukt disse strategiene, og unngått nevrale nettverk, dyp læring og AI så mye som mulig. Lær om hvordan ML brukes i forretningssystemer, økologiske applikasjoner, finans, kunst og kultur, og mer. diff --git a/translations/no/AGENTS.md b/translations/no/AGENTS.md index af4ef7ee2..00fe28f5f 100644 --- a/translations/no/AGENTS.md +++ b/translations/no/AGENTS.md @@ -1,12 +1,3 @@ - # AGENTS.md ## Prosjektoversikt diff --git a/translations/no/CODE_OF_CONDUCT.md b/translations/no/CODE_OF_CONDUCT.md index 6af71a60b..ca108b83a 100644 --- a/translations/no/CODE_OF_CONDUCT.md +++ b/translations/no/CODE_OF_CONDUCT.md @@ -1,12 +1,3 @@ - # Microsoft Open Source Code of Conduct Dette prosjektet har tatt i bruk [Microsoft Open Source Code of Conduct](https://opensource.microsoft.com/codeofconduct/). diff --git a/translations/no/CONTRIBUTING.md b/translations/no/CONTRIBUTING.md index 3c99f637b..e5e35a3b8 100644 --- a/translations/no/CONTRIBUTING.md +++ b/translations/no/CONTRIBUTING.md @@ -1,12 +1,3 @@ - # Bidra Dette prosjektet ønsker bidrag og forslag velkommen. De fleste bidrag krever at du diff --git a/translations/no/README.md b/translations/no/README.md index 1beb6fc49..4a31c872f 100644 --- a/translations/no/README.md +++ b/translations/no/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/) @@ -17,16 +8,16 @@ 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/) -### 🌐 Støtte for flere språk +### 🌐 Flerspråklig støtte #### Støttet via GitHub Action (Automatisert & Alltid Oppdatert) -[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](./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) +[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](./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)](../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) > **Foretrekker du å klone lokalt?** -> Dette depotet inkluderer over 50 språkoversettelser som betydelig øker nedlastingsstørrelsen. For å klone uten oversettelser, bruk sparsommelig utsjekking: +> Dette depotet inkluderer over 50 språkoversettelser som betydelig øker nedlastingsstørrelsen. For å klone uten oversettelser, bruk sparse checkout: > ```bash > git clone --filter=blob:none --sparse https://github.com/microsoft/ML-For-Beginners.git > cd ML-For-Beginners @@ -39,157 +30,157 @@ CO_OP_TRANSLATOR_METADATA: [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -Vi har en pågående Discord-lær med AI-serie, lær mer og bli med oss på [Learn with AI Series](https://aka.ms/learnwithai/discord) fra 18. - 30. september 2025. Du får tips og triks for å bruke GitHub Copilot for Data Science. +Vi har en Discord-lær-med-AI-serie pågående, lær mer og bli med oss på [Learn with AI Series](https://aka.ms/learnwithai/discord) fra 18. til 30. september 2025. Du vil få tips og triks for å bruke GitHub Copilot for Data Science. -![Learn with AI series](../../../../translated_images/no/3.9b58fd8d6c373c20.webp) +![Learn with AI series](../../translated_images/no/3.9b58fd8d6c373c20.webp) -# Maskinlæring for nybegynnere - En pensum +# Maskinlæring for nybegynnere - En læreplan > 🌍 Reis rundt i verden mens vi utforsker maskinlæring gjennom verdens kulturer 🌍 -Cloud Advocates hos Microsoft tilbyr et 12-ukers, 26-leksjoners pensum som handler om **maskinlæring**. I dette pensumet lærer du om det som noen ganger kalles **klassisk maskinlæring**, hvor vi primært bruker Scikit-learn som bibliotek og unngår dyp læring, som dekkes i vår [AI for Beginners' curriculum](https://aka.ms/ai4beginners). Kombiner gjerne disse leksjonene med vårt ['Data Science for Beginners' curriculum](https://aka.ms/ds4beginners) også! +Cloud Advocates hos Microsoft tilbyr en 12-ukers læreplan med 26 leksjoner som handler om **maskinlæring**. I denne læreplanen vil du lære om det som noen ganger kalles **klassisk maskinlæring**, med hovedfokus på Scikit-learn som bibliotek og uten å dekke dyp læring, som dekkes i vår [AI for Beginners-læreplan](https://aka.ms/ai4beginners). Kombiner disse leksjonene med vår ['Data Science for Beginners'-læreplan](https://aka.ms/ds4beginners) også! -Reis med oss rundt i verden mens vi anvender disse klassiske teknikkene på data fra mange områder av verden. Hver leksjon inkluderer forhånds- og etterquizzer, skriftlige instruksjoner for å fullføre leksjonen, en løsning, en oppgave og mer. Vår prosjektbaserte pedagogikk gjør at du lærer mens du bygger, en velkjent metode for at nye ferdigheter skal «sette seg». +Reis med oss rundt i verden mens vi anvender disse klassiske teknikkene på data fra mange deler av verden. Hver leksjon inkluderer før- og etter-leksjon quiz, skrevne instruksjoner for å fullføre leksjonen, en løsning, en oppgave og mer. Vår prosjektbaserte pedagogikk lar deg lære mens du bygger – en bevist metode for at nye ferdigheter skal 'sette seg'. **✍️ Hjertelig takk til våre forfattere** Jen Looper, Stephen Howell, Francesca Lazzeri, Tomomi Imura, Cassie Breviu, Dmitry Soshnikov, Chris Noring, Anirban Mukherjee, Ornella Altunyan, Ruth Yakubu og Amy Boyd -**🎨 Takk også til våre illustratører** Tomomi Imura, Dasani Madipalli og Jen Looper +**🎨 Takk også til våre illustratører** Tomomi Imura, Dasani Madipalli, og Jen Looper -**🙏 Spesiell takk 🙏 til våre Microsoft Student Ambassador-forfattere, anmeldere og innholdsbidragsytere**, spesielt Rishit Dagli, Muhammad Sakib Khan Inan, Rohan Raj, Alexandru Petrescu, Abhishek Jaiswal, Nawrin Tabassum, Ioan Samuila, og Snigdha Agarwal +**🙏 Spesiell takk 🙏 til våre Microsoft Student Ambassador-forfattere, -anmeldere og -innholdsbidragsytere**, særlig Rishit Dagli, Muhammad Sakib Khan Inan, Rohan Raj, Alexandru Petrescu, Abhishek Jaiswal, Nawrin Tabassum, Ioan Samuila og Snigdha Agarwal -**🤩 Ekstra takk til Microsoft Student Ambassadors Eric Wanjau, Jasleen Sondhi og Vidushi Gupta for våre R-leksjoner!** +**🤩 Ekstra takk til Microsoft Student Ambassadors Eric Wanjau, Jasleen Sondhi, og Vidushi Gupta for våre R-leksjoner!** # Komme i gang -Følg disse trinnene: +Følg disse stegene: 1. **Fork depotet**: Klikk på "Fork"-knappen øverst til høyre på denne siden. -2. **Klone depotet**: `git clone https://github.com/microsoft/ML-For-Beginners.git` +2. **Klone depotet**: `git clone https://github.com/microsoft/ML-For-Beginners.git` > [finn alle tilleggsmaterialer for dette kurset i vår Microsoft Learn-samling](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) -> 🔧 **Trenger du hjelp?** Sjekk vår [Feilsøkingsguide](TROUBLESHOOTING.md) for løsninger på vanlige problemer med installasjon, oppsett og kjøring av leksjoner. +> 🔧 **Trenger du hjelp?** Sjekk vår [Feilsøkingsveiledning](TROUBLESHOOTING.md) for løsninger på vanlige problemer med installasjon, oppsett og kjøring av leksjoner. -**[Studenter](https://aka.ms/student-page)**, for å bruke dette pensumet, fork hele repoen til din egen GitHub-konto og fullfør oppgavene alene eller i gruppe: +**[Studenter](https://aka.ms/student-page)**, for å bruke denne læreplanen, fork hele repoen til din egen GitHub-konto og fullfør øvelsene selv eller i gruppe: -- Start med en quiz før forelesningen. -- Les forelesningen og utfør aktivitetene, stopp opp og reflekter ved hvert kunnskapssjekkpunkt. -- Prøv å lage prosjektene ved å forstå leksjonene i stedet for å kjøre løsningskoden; denne koden er imidlertid tilgjengelig i `/solution`-mappene i hver prosjektorienterte leksjon. -- Ta quizzen etter forelesningen. +- Start med en før-forelesning quiz. +- Les forelesningen og fullfør aktivitetene, stopp opp og reflekter ved hver kunnskapskontroll. +- Prøv å lage prosjektene ved å forstå leksjonene, i stedet for å bare kjøre løsningskoden; den koden er likevel tilgjengelig i `/solution`-mappene i hver prosjektorientert leksjon. +- Ta etter-forelesning quiz. - Fullfør utfordringen. - Fullfør oppgaven. -- Etter å ha fullført en leksjonsgruppe, besøk [Diskusjonstavlen](https://github.com/microsoft/ML-For-Beginners/discussions) og «lær høyt» ved å fylle ut den passende PAT-rubriken. En 'PAT' er et fremdriftsvurderingsverktøy som er en rubrikk du fyller ut for å fremme læringen din. Du kan også reagere på andre PAT-er slik at vi kan lære sammen. +- Etter å ha fullført en leksjonsgruppe, besøk [Diskusjonsforumet](https://github.com/microsoft/ML-For-Beginners/discussions) og "lær høyt" ved å fylle ut det aktuelle PAT-skjemaet. En 'PAT' er et fremdriftsevalueringsverktøy som er et skjema du fyller ut for å fremme læringen. Du kan også reagere på andres PAT-er slik at vi kan lære sammen. > For videre studier anbefaler vi å følge disse [Microsoft Learn](https://docs.microsoft.com/en-us/users/jenlooper-2911/collections/k7o7tg1gp306q4?WT.mc_id=academic-77952-leestott) modulene og læringsløpene. -**Lærere**, vi har [inkludert noen forslag](for-teachers.md) om hvordan du kan bruke dette pensumet. +**Lærere**, vi har [inkludert noen forslag](for-teachers.md) til hvordan man kan bruke denne læreplanen. --- -## Videofremvisninger +## Videogjennomganger -Noen av leksjonene er tilgjengelige som korte videoer. Du finner alle disse innebygd i leksjonene, eller på [ML for Beginners-spillelisten på Microsoft Developer YouTube-kanalen](https://aka.ms/ml-beginners-videos) ved å klikke på bildet nedenfor. +Noen av leksjonene finnes som korte videoer. Du kan finne alle disse innebygd i leksjonene, eller på [ML for Beginners-spillelisten på Microsoft Developer YouTube-kanalen](https://aka.ms/ml-beginners-videos) ved å klikke på bildet nedenfor. -[![ML for beginners banner](../../../../translated_images/no/ml-for-beginners-video-banner.63f694a100034bc6.webp)](https://aka.ms/ml-beginners-videos) +[![ML for beginners banner](../../translated_images/no/ml-for-beginners-video-banner.63f694a100034bc6.webp)](https://aka.ms/ml-beginners-videos) --- ## Møt teamet -[![Promo video](../../images/ml.gif)](https://youtu.be/Tj1XWrDSYJU) +[![Promovideo](../../images/ml.gif)](https://youtu.be/Tj1XWrDSYJU) **Gif av** [Mohit Jaisal](https://linkedin.com/in/mohitjaisal) -> 🎥 Klikk på bildet ovenfor for en video om prosjektet og folkene som laget det! +> 🎥 Klikk på bildet over for en video om prosjektet og personene som skapte det! --- ## Pedagogikk -Vi har valgt to pedagogiske prinsipper under byggingen av dette pensumet: å sikre at det er praktisk **prosjektbasert** og at det inneholder **hyppige quizzer**. I tillegg har dette pensumet et felles **tema** for å gi det sammenheng. +Vi har valgt to pedagogiske prinsipper under utviklingen av denne læreplanen: å sikre at den er praktisk **prosjektbasert** og at den inkluderer **hyppige quizzer**. I tillegg har denne læreplanen et felles **tema** for å gi den sammenheng. -Ved å sikre at innholdet er knyttet til prosjekter, blir prosessen mer engasjerende for studentene og konseptene blir bedre lagret. I tillegg setter en lavterskel-quiz før undervisningen studentens intensjon mot å lære et emne, mens en andre quiz etter undervisning sikrer ytterligere lagring. Dette pensumet er designet for å være fleksibelt og morsomt og kan tas i sin helhet eller delvis. Prosjektene starter smått og blir gradvis mer kompliserte mot slutten av den 12-ukers syklusen. Dette pensumet inkluderer også et etterord om virkelige anvendelser av ML, som kan brukes som ekstra oppgaver eller som basis for diskusjon. +Ved å sørge for at innholdet samsvarer med prosjekter, gjøres prosessen mer engasjerende for studentene og vil bedre bidra til at konseptene huskes. I tillegg setter en lavterskel quiz før timen intensjonen til studenten mot å lære et tema, mens en andre quiz etter timen sikrer videre lagring. Denne læreplanen er designet for å være fleksibel og morsom, og kan tas i sin helhet eller delvis. Prosjektene starter smått og blir gradvis mer komplekse mot slutten av 12-ukers syklusen. Læreplanen inkluderer også et etterord om virkelige anvendelser av maskinlæring, som kan brukes som ekstra poeng eller som grunnlag for diskusjon. -> Finn våre retningslinjer for [oppførselskode](CODE_OF_CONDUCT.md), [bidrag](CONTRIBUTING.md), [oversettelse](TRANSLATIONS.md) og [feilsøking](TROUBLESHOOTING.md). Vi tar imot konstruktive tilbakemeldinger! +> Finn våre [Regler for god oppførsel](CODE_OF_CONDUCT.md), [Bidrag](CONTRIBUTING.md), [Oversettelse](TRANSLATIONS.md) og [Feilsøking](TROUBLESHOOTING.md) retningslinjer. Vi setter pris på din konstruktive tilbakemelding! ## Hver leksjon inkluderer -- valgfri skisse +- valgfri skisse-illustrasjon - valgfri tilleggsvideo -- video gjennomgang (kun noen leksjoner) -- [quiz før forelesning](https://ff-quizzes.netlify.app/en/ml/) +- videogjennomgang (kun noen leksjoner) +- [oppvarmingsquiz før forelesning](https://ff-quizzes.netlify.app/en/ml/) - skriftlig leksjon -- for prosjektbaserte leksjoner, steg-for-steg guider for å bygge prosjektet -- kunnskapssjekker +- for prosjektbaserte leksjoner, steg-for-steg guider på hvordan man bygger prosjektet +- kunnskapskontroller - en utfordring -- tilleggslesning +- tilleggstekster - oppgave - [quiz etter forelesning](https://ff-quizzes.netlify.app/en/ml/) -> **En merknad om språk**: Disse leksjonene er primært skrevet i Python, men mange finnes også i R. For å fullføre en R-leksjon, gå til `/solution`-mappen og se etter R-leksjoner. De inkluderer en .rmd-utvidelse som representerer en **R Markdown**-fil, som enkelt kan defineres som en innbygging av `kodebiter` (av R eller andre språk) og en `YAML-topptekst` (som styrer hvordan utdata formateres som PDF) i et `Markdown-dokument`. Som sådan fungerer det som en eksemplarisk ramme for å skrive for data science, siden det lar deg kombinere koden din, dens output og dine tanker ved å la deg skrive dem ned i Markdown. Videre kan R Markdown-dokumenter gjengis til utdataformater som PDF, HTML eller Word. -> **En merknad om quizzer**: Alle quizzer finnes i [Quiz App-mappen](../../quiz-app), med totalt 52 quizer med tre spørsmål hver. De er lenket fra leksjonene, men quiz-appen kan kjøres lokalt; følg instruksjonene i `quiz-app`-mappen for å kjøre lokalt eller distribuere til Azure. - -| Leksjonsnummer | Emne | Leksjonsgruppering | Læringsmål | Tilknyttet leksjon | Forfatter | -| :------------: | :----------------------------------------------------------: | :----------------------------------------------------: | ---------------------------------------------------------------------------------------------------------------------------- | :-----------------------------------------------------------------------------------------------------------------------------------------: | :----------------------------------------------------: | -| 01 | Introduksjon til maskinlæring | [Introduksjon](1-Introduction/README.md) | Lær de grunnleggende konseptene bak maskinlæring | [Leksjon](1-Introduction/1-intro-to-ML/README.md) | Muhammad | -| 02 | Maskinlæringens historie | [Introduksjon](1-Introduction/README.md) | Lær historien bak dette feltet | [Leksjon](1-Introduction/2-history-of-ML/README.md) | Jen og Amy | -| 03 | Rettferdighet og maskinlæring | [Introduksjon](1-Introduction/README.md) | Hva er de viktige filosofiske spørsmålene rundt rettferdighet som studenter bør vurdere ved bygging og bruk av ML-modeller? | [Leksjon](1-Introduction/3-fairness/README.md) | Tomomi | -| 04 | Teknikker for maskinlæring | [Introduksjon](1-Introduction/README.md) | Hvilke teknikker bruker ML-forskere for å bygge ML-modeller? | [Leksjon](1-Introduction/4-techniques-of-ML/README.md) | Chris og Jen | -| 05 | Introduksjon til regresjon | [Regresjon](2-Regression/README.md) | Kom i gang med Python og Scikit-learn for regresjonsmodeller | [Python](2-Regression/1-Tools/README.md) • [R](../../2-Regression/1-Tools/solution/R/lesson_1.html) | Jen • Eric Wanjau | -| 06 | Priser på gresskar i Nord-Amerika 🎃 | [Regresjon](2-Regression/README.md) | Visualiser og rens data som forberedelse til ML | [Python](2-Regression/2-Data/README.md) • [R](../../2-Regression/2-Data/solution/R/lesson_2.html) | Jen • Eric Wanjau | -| 07 | Priser på gresskar i Nord-Amerika 🎃 | [Regresjon](2-Regression/README.md) | Bygg lineære og polynomiale regresjonsmodeller | [Python](2-Regression/3-Linear/README.md) • [R](../../2-Regression/3-Linear/solution/R/lesson_3.html) | Jen og Dmitry • Eric Wanjau | -| 08 | Priser på gresskar i Nord-Amerika 🎃 | [Regresjon](2-Regression/README.md) | Bygg en logistisk regresjonsmodell | [Python](2-Regression/4-Logistic/README.md) • [R](../../2-Regression/4-Logistic/solution/R/lesson_4.html) | Jen • Eric Wanjau | -| 09 | En Web-applikasjon 🔌 | [Web App](3-Web-App/README.md) | Bygg en web-app for å bruke din trente modell | [Python](3-Web-App/1-Web-App/README.md) | Jen | -| 10 | Introduksjon til klassifisering | [Klassifisering](4-Classification/README.md) | Rens, klargjør og visualiser dine data; introduksjon til klassifisering | [Python](4-Classification/1-Introduction/README.md) • [R](../../4-Classification/1-Introduction/solution/R/lesson_10.html) | Jen og Cassie • Eric Wanjau | -| 11 | Deilige asiatiske og indiske kjøkken 🍜 | [Klassifisering](4-Classification/README.md) | Introduksjon til klassifikatorer | [Python](4-Classification/2-Classifiers-1/README.md) • [R](../../4-Classification/2-Classifiers-1/solution/R/lesson_11.html) | Jen og Cassie • Eric Wanjau | -| 12 | Deilige asiatiske og indiske kjøkken 🍜 | [Klassifisering](4-Classification/README.md) | Flere klassifikatorer | [Python](4-Classification/3-Classifiers-2/README.md) • [R](../../4-Classification/3-Classifiers-2/solution/R/lesson_12.html) | Jen og Cassie • Eric Wanjau | -| 13 | Deilige asiatiske og indiske kjøkken 🍜 | [Klassifisering](4-Classification/README.md) | Bygg en anbefalingsweb-app basert på modellen din | [Python](4-Classification/4-Applied/README.md) | Jen | -| 14 | Introduksjon til klynging | [Klynging](5-Clustering/README.md) | Rens, klargjør og visualiser dine data; introduksjon til klynging | [Python](5-Clustering/1-Visualize/README.md) • [R](../../5-Clustering/1-Visualize/solution/R/lesson_14.html) | Jen • Eric Wanjau | -| 15 | Utforske musikksmaken i Nigeria 🎧 | [Klynging](5-Clustering/README.md) | Utforsk K-Means klyngemetoden | [Python](5-Clustering/2-K-Means/README.md) • [R](../../5-Clustering/2-K-Means/solution/R/lesson_15.html) | Jen • Eric Wanjau | -| 16 | Introduksjon til naturlig språkbehandling ☕️ | [Naturlig språkbehandling](6-NLP/README.md) | Lær grunnleggende om NLP ved å bygge en enkel bot | [Python](6-NLP/1-Introduction-to-NLP/README.md) | Stephen | -| 17 | Vanlige NLP-oppgaver ☕️ | [Naturlig språkbehandling](6-NLP/README.md) | Fordyp deg i NLP ved å forstå vanlige oppgaver som kreves ved språkstrukturer | [Python](6-NLP/2-Tasks/README.md) | Stephen | -| 18 | Oversettelse og sentimentanalyse ♥️ | [Naturlig språkbehandling](6-NLP/README.md) | Oversettelse og sentimentanalyse med Jane Austen | [Python](6-NLP/3-Translation-Sentiment/README.md) | Stephen | -| 19 | Romantiske hoteller i Europa ♥️ | [Naturlig språkbehandling](6-NLP/README.md) | Sentimentanalyse med hotellanmeldelser 1 | [Python](6-NLP/4-Hotel-Reviews-1/README.md) | Stephen | -| 20 | Romantiske hoteller i Europa ♥️ | [Naturlig språkbehandling](6-NLP/README.md) | Sentimentanalyse med hotellanmeldelser 2 | [Python](6-NLP/5-Hotel-Reviews-2/README.md) | Stephen | -| 21 | Introduksjon til tidsserieprognoser | [Tidsserie](7-TimeSeries/README.md) | Introduksjon til tidsserieprognoser | [Python](7-TimeSeries/1-Introduction/README.md) | Francesca | -| 22 | ⚡️ Verdens strømforbruk ⚡️ - tidsserieprognoser med ARIMA | [Tidsserie](7-TimeSeries/README.md) | Tidsserieprognoser med ARIMA | [Python](7-TimeSeries/2-ARIMA/README.md) | Francesca | -| 23 | ⚡️ Verdens strømforbruk ⚡️ - tidsserieprognoser med SVR | [Tidsserie](7-TimeSeries/README.md) | Tidsserieprognoser med Support Vector Regressor | [Python](7-TimeSeries/3-SVR/README.md) | Anirban | -| 24 | Introduksjon til forsterkningslæring | [Forsterkningslæring](8-Reinforcement/README.md) | Introduksjon til forsterkningslæring med Q-Learning | [Python](8-Reinforcement/1-QLearning/README.md) | Dmitry | -| 25 | Hjelp Peter med å unngå ulven! 🐺 | [Forsterkningslæring](8-Reinforcement/README.md) | Forsterkningslæring Gym | [Python](8-Reinforcement/2-Gym/README.md) | Dmitry | -| Postscript | Virkelige ML-scenarier og -anvendelser | [ML i det fri](9-Real-World/README.md) | Interessante og avslørende virkelige anvendelser for klassisk ML | [Leksjon](9-Real-World/1-Applications/README.md) | Team | -| Postscript | Modellfeilsøking i ML med RAI dashboard | [ML i det fri](9-Real-World/README.md) | Modellfeilsøking i maskinlæring med Responsible AI dashboard-komponenter | [Leksjon](9-Real-World/2-Debugging-ML-Models/README.md) | Ruth Yakubu | +> **En notis om språk**: Disse leksjonene er hovedsakelig skrevet i Python, men mange finnes også på R. For å fullføre en R-leksjon, gå til `/solution`-mappen og se etter R-leksjoner. De har en .rmd-utvidelse som representerer en **R Markdown**-fil, som enkelt kan defineres som en innbedding av `kodebiter` (av R eller andre språk) og en `YAML-header` (som styrer hvordan utdata formateres, som PDF) i et `Markdown-dokument`. Som sådan fungerer det som en eksemplarisk forfatterramme for datafag siden det lar deg kombinere koden din, dens utdata og dine tanker ved at du kan skrive dem ned i Markdown. Videre kan R Markdown-dokumenter gjengis til utdataformater som PDF, HTML eller Word. +> **En merknad om quizzer**: Alle quizzer finnes i [Quiz App folder](../../quiz-app), totalt 52 quizer med tre spørsmål hver. De er lenket fra leksjonene, men quiz appen kan kjøres lokalt; følg instruksjonene i `quiz-app`-mappen for lokal hosting eller distribusjon til Azure. + +| Lesson Number | Topic | Lesson Grouping | Learning Objectives | Linked Lesson | Author | +| :-----------: | :------------------------------------------------------------: | :-------------------------------------------------: | ------------------------------------------------------------------------------------------------------------------------------- | :--------------------------------------------------------------------------------------------------------------------------------------: | :--------------------------------------------------: | +| 01 | Introduksjon til maskinlæring | [Introduction](1-Introduction/README.md) | Lær de grunnleggende konseptene bak maskinlæring | [Lesson](1-Introduction/1-intro-to-ML/README.md) | Muhammad | +| 02 | Historien om maskinlæring | [Introduction](1-Introduction/README.md) | Lær historien bak dette feltet | [Lesson](1-Introduction/2-history-of-ML/README.md) | Jen and Amy | +| 03 | Rettferdighet og maskinlæring | [Introduction](1-Introduction/README.md) | Hva er de viktige filosofiske spørsmålene rundt rettferdighet som studenter bør vurdere når de bygger og bruker ML-modeller? | [Lesson](1-Introduction/3-fairness/README.md) | Tomomi | +| 04 | Teknikker for maskinlæring | [Introduction](1-Introduction/README.md) | Hvilke teknikker bruker ML-forskere for å bygge ML-modeller? | [Lesson](1-Introduction/4-techniques-of-ML/README.md) | Chris and Jen | +| 05 | Introduksjon til regresjon | [Regression](2-Regression/README.md) | Kom i gang med Python og Scikit-learn for regresjonsmodeller | [Python](2-Regression/1-Tools/README.md) • [R](../../2-Regression/1-Tools/solution/R/lesson_1.html) | Jen • Eric Wanjau | +| 06 | Nord-amerikanske gresskarpriser 🎃 | [Regression](2-Regression/README.md) | Visualiser og rens data i forberedelse til ML | [Python](2-Regression/2-Data/README.md) • [R](../../2-Regression/2-Data/solution/R/lesson_2.html) | Jen • Eric Wanjau | +| 07 | Nord-amerikanske gresskarpriser 🎃 | [Regression](2-Regression/README.md) | Bygg lineære og polynomiske regresjonsmodeller | [Python](2-Regression/3-Linear/README.md) • [R](../../2-Regression/3-Linear/solution/R/lesson_3.html) | Jen and Dmitry • Eric Wanjau | +| 08 | Nord-amerikanske gresskarpriser 🎃 | [Regression](2-Regression/README.md) | Bygg en logistisk regresjonsmodell | [Python](2-Regression/4-Logistic/README.md) • [R](../../2-Regression/4-Logistic/solution/R/lesson_4.html) | Jen • Eric Wanjau | +| 09 | En webapp 🔌 | [Web App](3-Web-App/README.md) | Bygg en webapp for å bruke den trente modellen | [Python](3-Web-App/1-Web-App/README.md) | Jen | +| 10 | Introduksjon til klassifisering | [Classification](4-Classification/README.md) | Rens, forbered og visualiser data; introduksjon til klassifisering | [Python](4-Classification/1-Introduction/README.md) • [R](../../4-Classification/1-Introduction/solution/R/lesson_10.html) | Jen and Cassie • Eric Wanjau | +| 11 | Deilige asiatiske og indiske retter 🍜 | [Classification](4-Classification/README.md) | Introduksjon til klassifikatorer | [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 | Deilige asiatiske og indiske retter 🍜 | [Classification](4-Classification/README.md) | Flere klassifikatorer | [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 | Deilige asiatiske og indiske retter 🍜 | [Classification](4-Classification/README.md) | Bygg en anbefalings-webapp ved hjelp av modellen din | [Python](4-Classification/4-Applied/README.md) | Jen | +| 14 | Introduksjon til klynging | [Clustering](5-Clustering/README.md) | Rens, forbered og visualiser data; introduksjon til klynging | [Python](5-Clustering/1-Visualize/README.md) • [R](../../5-Clustering/1-Visualize/solution/R/lesson_14.html) | Jen • Eric Wanjau | +| 15 | Utforskning av nigerianske musikksmaker 🎧 | [Clustering](5-Clustering/README.md) | Utforsk K-Means klyngealgoritmen | [Python](5-Clustering/2-K-Means/README.md) • [R](../../5-Clustering/2-K-Means/solution/R/lesson_15.html) | Jen • Eric Wanjau | +| 16 | Introduksjon til naturlig språkbehandling ☕️ | [Natural language processing](6-NLP/README.md) | Lær det grunnleggende om NLP ved å bygge en enkel bot | [Python](6-NLP/1-Introduction-to-NLP/README.md) | Stephen | +| 17 | Vanlige NLP-oppgaver ☕️ | [Natural language processing](6-NLP/README.md) | Fordyp kunnskapen din om NLP ved å forstå vanlige oppgaver som kreves når man håndterer språkstrukturer | [Python](6-NLP/2-Tasks/README.md) | Stephen | +| 18 | Oversettelse og sentimentanalyse ♥️ | [Natural language processing](6-NLP/README.md) | Oversettelse og sentimentanalyse med Jane Austen | [Python](6-NLP/3-Translation-Sentiment/README.md) | Stephen | +| 19 | Romantiske hoteller i Europa ♥️ | [Natural language processing](6-NLP/README.md) | Sentimentanalyse med hotellvurderinger 1 | [Python](6-NLP/4-Hotel-Reviews-1/README.md) | Stephen | +| 20 | Romantiske hoteller i Europa ♥️ | [Natural language processing](6-NLP/README.md) | Sentimentanalyse med hotellvurderinger 2 | [Python](6-NLP/5-Hotel-Reviews-2/README.md) | Stephen | +| 21 | Introduksjon til tidsserieprognoser | [Time series](7-TimeSeries/README.md) | Introduksjon til tidsserieprognoser | [Python](7-TimeSeries/1-Introduction/README.md) | Francesca | +| 22 | ⚡️ Verdens strømforbruk ⚡️ - tidsserieprognoser med ARIMA | [Time series](7-TimeSeries/README.md) | Tidsserieprognoser med ARIMA | [Python](7-TimeSeries/2-ARIMA/README.md) | Francesca | +| 23 | ⚡️ Verdens strømforbruk ⚡️ - tidsserieprognoser med SVR | [Time series](7-TimeSeries/README.md) | Tidsserieprognoser med Support Vector Regressor | [Python](7-TimeSeries/3-SVR/README.md) | Anirban | +| 24 | Introduksjon til forsterkningslæring | [Reinforcement learning](8-Reinforcement/README.md) | Introduksjon til forsterkningslæring med Q-Learning | [Python](8-Reinforcement/1-QLearning/README.md) | Dmitry | +| 25 | Hjelp Peter å unngå ulven! 🐺 | [Reinforcement learning](8-Reinforcement/README.md) | Gym for forsterkningslæring | [Python](8-Reinforcement/2-Gym/README.md) | Dmitry | +| Postscript | Virkelige ML-scenarier og anvendelser | [ML in the Wild](9-Real-World/README.md) | Interessante og avslørende virkelige anvendelser av klassisk ML | [Lesson](9-Real-World/1-Applications/README.md) | Team | +| Postscript | Feilsøking av modeller i ML ved bruk av RAI dashboard | [ML in the Wild](9-Real-World/README.md) | Feilsøking av modeller i maskinlæring ved bruk av Responsible AI-dashboard komponenter | [Lesson](9-Real-World/2-Debugging-ML-Models/README.md) | Ruth Yakubu | > [finn alle tilleggsmaterialer for dette kurset i vår Microsoft Learn-samling](https://learn.microsoft.com/en-us/collections/qrqzamz1nn2wx3?WT.mc_id=academic-77952-bethanycheum) ## Offline tilgang -Du kan kjøre denne dokumentasjonen offline ved å bruke [Docsify](https://docsify.js.org/#/). Fork dette depotet, [installer Docsify](https://docsify.js.org/#/quickstart) på din lokale maskin, og deretter i rotmappen for dette depotet, skriv `docsify serve`. Nettstedet vil bli servert på port 3000 lokalt: `localhost:3000`. +Du kan kjøre denne dokumentasjonen offline ved å bruke [Docsify](https://docsify.js.org/#/). Fork dette repoet, [installer Docsify](https://docsify.js.org/#/quickstart) på din lokale maskin, og skriv deretter `docsify serve` i rotmappen av dette repoet. Nettstedet vil kjøre på port 3000 på din localhost: `localhost:3000`. -## PDFer +## PDF-er -Finn en pdf av pensum med lenker [her](https://microsoft.github.io/ML-For-Beginners/pdf/readme.pdf). +Finn en pdf av lærematerialet med lenker [her](https://microsoft.github.io/ML-For-Beginners/pdf/readme.pdf). ## 🎒 Andre kurs -Vårt team lager andre kurs! Sjekk ut: +Vårt team produserer andre kurs! Sjekk ut: ### LangChain -[![LangChain4j for nybegynnere](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 nybegynnere](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 / Agenter -[![AZD for nybegynnere](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 nybegynnere](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 nybegynnere](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-agenter for nybegynnere](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) --- -### Generative AI-serien +### Generative AI Series [![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) @@ -197,7 +188,7 @@ Vårt team lager andre kurs! Sjekk ut: --- -### Kjerneopplæring +### Kjernelæring [![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) @@ -208,7 +199,7 @@ Vårt team lager andre kurs! Sjekk ut: --- -### Copilot-serie +### Copilot-serien [![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) @@ -216,11 +207,11 @@ Vårt team lager andre kurs! Sjekk ut: ## Få hjelp -Hvis du står fast eller har spørsmål om å bygge AI-apper. Bli med andre elever og erfarne utviklere i diskusjoner om MCP. Det er et støttende fellesskap hvor spørsmål er velkomne og kunnskap deles fritt. +Hvis du setter deg fast eller har spørsmål om å bygge AI-apper. Bli med andre lærende og erfarne utviklere i diskusjoner om MCP. Det er et støttende fellesskap hvor spørsmål er velkomne og kunnskap deles fritt. [![Microsoft Foundry Discord](https://dcbadge.limes.pink/api/server/nTYy5BXMWG)](https://discord.gg/nTYy5BXMWG) -Hvis du har produktfeedback eller feil under bygging, besøk: +Hvis du har produktfeedback eller opplever feil under bygging, besøk: [![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) @@ -228,5 +219,5 @@ Hvis du har produktfeedback eller feil under bygging, besøk: **Ansvarsfraskrivelse**: -Dette dokumentet er oversatt ved hjelp av AI-oversettingstjenesten [Co-op Translator](https://github.com/Azure/co-op-translator). Selv om vi streber etter nøyaktighet, vennligst vær oppmerksom på at automatiske oversettelser kan inneholde feil eller unøyaktigheter. Det opprinnelige dokumentet på dets opprinnelige språk bør anses som den autoritative kilden. For kritisk informasjon anbefales profesjonell menneskelig oversettelse. Vi er ikke ansvarlige for misforståelser eller feiltolkninger som oppstår ved bruk av denne oversettelsen. +Dette dokumentet er oversatt ved hjelp av AI-oversettelsestjenesten [Co-op Translator](https://github.com/Azure/co-op-translator). Selv om vi streber etter nøyaktighet, vær oppmerksom på at automatiske oversettelser kan inneholde feil eller unøyaktigheter. Det originale dokumentet på sitt opprinnelige språk skal anses som den autoritative kilden. For kritisk informasjon anbefales profesjonell menneskelig oversettelse. Vi er ikke ansvarlige for eventuelle misforståelser eller feiltolkninger som oppstår ved bruk av denne oversettelsen. \ No newline at end of file diff --git a/translations/no/SECURITY.md b/translations/no/SECURITY.md index 924c18728..06eda3fa1 100644 --- a/translations/no/SECURITY.md +++ b/translations/no/SECURITY.md @@ -1,12 +1,3 @@ - ## Sikkerhet Microsoft tar sikkerheten til våre programvareprodukter og tjenester på alvor, inkludert alle kildekoderepositorier som administreres gjennom våre GitHub-organisasjoner, som inkluderer [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), og [våre GitHub-organisasjoner](https://opensource.microsoft.com/). diff --git a/translations/no/SUPPORT.md b/translations/no/SUPPORT.md index b6991a8bf..55208a144 100644 --- a/translations/no/SUPPORT.md +++ b/translations/no/SUPPORT.md @@ -1,12 +1,3 @@ - # Støtte ## Hvordan rapportere problemer og få hjelp diff --git a/translations/no/TROUBLESHOOTING.md b/translations/no/TROUBLESHOOTING.md index 6456d5512..51ace65c2 100644 --- a/translations/no/TROUBLESHOOTING.md +++ b/translations/no/TROUBLESHOOTING.md @@ -1,12 +1,3 @@ - # Feilsøkingsguide Denne guiden hjelper deg med å løse vanlige problemer når du jobber med Machine Learning for Beginners-kurset. Hvis du ikke finner en løsning her, kan du sjekke våre [Discord-diskusjoner](https://aka.ms/foundry/discord) eller [åpne en sak](https://github.com/microsoft/ML-For-Beginners/issues). diff --git a/translations/no/docs/_sidebar.md b/translations/no/docs/_sidebar.md index 39be138e1..17ec3512f 100644 --- a/translations/no/docs/_sidebar.md +++ b/translations/no/docs/_sidebar.md @@ -1,12 +1,3 @@ - - Introduksjon - [Introduksjon til maskinlæring](../1-Introduction/1-intro-to-ML/README.md) - [Historien om maskinlæring](../1-Introduction/2-history-of-ML/README.md) diff --git a/translations/no/for-teachers.md b/translations/no/for-teachers.md index 4d7e87fc8..52e29cf09 100644 --- a/translations/no/for-teachers.md +++ b/translations/no/for-teachers.md @@ -1,12 +1,3 @@ - ## For lærere Ønsker du å bruke dette pensumet i klasserommet ditt? Vær så god! diff --git a/translations/no/quiz-app/README.md b/translations/no/quiz-app/README.md index 18e179b98..4aa7f5e49 100644 --- a/translations/no/quiz-app/README.md +++ b/translations/no/quiz-app/README.md @@ -1,12 +1,3 @@ - # Quizer Disse quizene er forhånds- og etterforelesningsquizene for ML-læreplanen på https://aka.ms/ml-beginners diff --git a/translations/no/sketchnotes/LICENSE.md b/translations/no/sketchnotes/LICENSE.md index 617e125c2..cfde708be 100644 --- a/translations/no/sketchnotes/LICENSE.md +++ b/translations/no/sketchnotes/LICENSE.md @@ -1,12 +1,3 @@ - Attribution-ShareAlike 4.0 Internasjonal ======================================================================= diff --git a/translations/no/sketchnotes/README.md b/translations/no/sketchnotes/README.md index d997255f4..7b89bff2d 100644 --- a/translations/no/sketchnotes/README.md +++ b/translations/no/sketchnotes/README.md @@ -1,12 +1,3 @@ - Alle sketchnotes for pensum kan lastes ned her. 🖨 For utskrift i høy oppløsning er TIFF-versjonene tilgjengelige på [dette repoet](https://github.com/girliemac/a-picture-is-worth-a-1000-words/tree/main/ml/tiff).