diff --git a/2-Regression/1-Tools/README.md b/2-Regression/1-Tools/README.md index 9e2225dc..55e188db 100644 --- a/2-Regression/1-Tools/README.md +++ b/2-Regression/1-Tools/README.md @@ -10,9 +10,10 @@ Describe what we will learn ### Introduction -Describe what will be covered - -> Notes +In this lesson, you will learn: +- How to configure Visual Studio Code for machine learning tasks +- An introduction to Scikit-Learn, including installation +- Some tips on working with Python for ML ### Prerequisite diff --git a/2-Regression/1-Tools/notebook.ipynb b/2-Regression/1-Tools/notebook.ipynb new file mode 100644 index 00000000..e69de29b diff --git a/2-Regression/2-Data/README.md b/2-Regression/2-Data/README.md index 7f7b5ac3..befa659f 100644 --- a/2-Regression/2-Data/README.md +++ b/2-Regression/2-Data/README.md @@ -7,6 +7,7 @@ In this lesson, you will learn: - Good reasons to create a regression model for a machine learning problem +- Some math behind regression models - Using Scikit-Learn to evaluate your data - Preparing your data for training, testing, and evaluation diff --git a/2-Regression/2-Data/notebook.ipynb b/2-Regression/2-Data/notebook.ipynb new file mode 100644 index 00000000..e69de29b diff --git a/2-Regression/3-Linear/notebook.ipynb b/2-Regression/3-Linear/notebook.ipynb new file mode 100644 index 00000000..e69de29b diff --git a/2-Regression/4-Logistic/notebook.ipynb b/2-Regression/4-Logistic/notebook.ipynb new file mode 100644 index 00000000..e69de29b diff --git a/README.md b/README.md index 39201750..c07ce504 100644 --- a/README.md +++ b/README.md @@ -59,16 +59,16 @@ By ensuring that the content aligns with projects, the process is made more enga > **A note about quizzes**: All quizzes are contained [in this app](link a quiz app here), for 48 total quizzes of three questions each. They are linked from within the lessons but the quiz app can be run locally; follow the instruction in the `quiz-app` folder. -| Lesson Number | Project Name/Group | Concepts Taught | Learning Objectives | Linked Lesson | Author | -| :-----------: | :--------------------------------------: | :----------------------------------: | ---------------------------------------------------------------------------------------------------- | :-------------------------------------------: | :----: | -| 01 | [Introduction](1-Introduction/README.md) | Introduction to Machine Learning | Learn the basic concepts behind Machine Learning | [📓](1-Introduction/1-intro-to-ML/README.md) | Amy | -| 02 | [Introduction](1-Introduction/README.md) | The History of Machine Learning | Learn the history underlying this field | [📓](1-Introduction/2-history-of-ML/README.md) | Amy | -| 03 | North American Pumpkin Prices 🎃 | [Regression](2-Regression/README.md) | Get started with Python and Scikit-Learn for Regression models | [📓](2-Regression/1-Tools/README.md) | Jen | -| 04 | North American Pumpkin Prices 🎃 | [Regression](2-Regression/README.md) | Visualize and clean data in preparation for ML | [📓](2-Regression/2-Data/README.md) | Jen | -| 05 | North American Pumpkin Prices 🎃 | [Regression](2-Regression/README.md) | Build a Linear Regression model | [📓](2-Regression/3-Linear/README.md) | Jen | -| 06 | North American Pumpkin Prices 🎃 | [Regression](2-Regression/README.md) | Build a Logistic Regression model | [📓](2-Regression/4-Logistic/README.md) | Jen | -| 23 | Future | The Ethics of Machine Learning | What are the important ethical issues apparent now and how will they impact the field going forward? | [📓](8-Future/Ethics/README.md) | | -| 24 | Future | The Future of Machine Learning | What are the important trends that will shape the future of ML? | [📓](8-Future/Future-Trends/README.md) | | +| Lesson Number | Project Name/Group | Concepts Taught | Learning Objectives | Linked Lesson | Author | +| :-----------: | :--------------------------------------: | :----------------------------------: | ---------------------------------------------------------------------------------------------------- | :------------------------------------------------: | :----: | +| 01 | [Introduction](1-Introduction/README.md) | Introduction to Machine Learning | Learn the basic concepts behind Machine Learning | [lesson](1-Introduction/1-intro-to-ML/README.md) | Amy | +| 02 | [Introduction](1-Introduction/README.md) | The History of Machine Learning | Learn the history underlying this field | [lesson](1-Introduction/2-history-of-ML/README.md) | Amy | +| 03 | North American Pumpkin Prices 🎃 | [Regression](2-Regression/README.md) | Get started with Python and Scikit-Learn for Regression models | [lesson](2-Regression/1-Tools/README.md) | Jen | +| 04 | North American Pumpkin Prices 🎃 | [Regression](2-Regression/README.md) | Visualize and clean data in preparation for ML | [lesson](2-Regression/2-Data/README.md) | Jen | +| 05 | North American Pumpkin Prices 🎃 | [Regression](2-Regression/README.md) | Build a Linear Regression model | [lesson](2-Regression/3-Linear/README.md) | Jen | +| 06 | North American Pumpkin Prices 🎃 | [Regression](2-Regression/README.md) | Build a Logistic Regression model | [lesson](2-Regression/4-Logistic/README.md) | Jen | +| 23 | Future | The Ethics of Machine Learning | What are the important ethical issues apparent now and how will they impact the field going forward? | [lesson](8-Future/Ethics/README.md) | | +| 24 | Future | The Future of Machine Learning | What are the important trends that will shape the future of ML? | [lesson](8-Future/Future-Trends/README.md) | | ## Offline access You can run this documentation offline by using [Docsify](https://docsify.js.org/#/). 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