> 🎥 Click the image above for a video about the project and the folks who created it!
> 🎥 Click the image above for a video about the project and the folks who created it!
@ -78,7 +80,7 @@ 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](https://white-water-09ec41f0f.azurestaticapps.net/), for 52 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.
> **A note about quizzes**: All quizzes are contained [in this app](https://white-water-09ec41f0f.azurestaticapps.net/), for 52 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.
| 01 | Introduction to machine learning | [Introduction](1-Introduction/README.md) | Learn the basic concepts behind machine learning | [Lesson](1-Introduction/1-intro-to-ML/README.md) | Muhammad |
| 01 | Introduction to machine learning | [Introduction](1-Introduction/README.md) | Learn the basic concepts behind machine learning | [Lesson](1-Introduction/1-intro-to-ML/README.md) | Muhammad |
| 02 | The History of machine learning | [Introduction](1-Introduction/README.md) | Learn the history underlying this field | [Lesson](1-Introduction/2-history-of-ML/README.md) | Jen and Amy |
| 02 | The History of machine learning | [Introduction](1-Introduction/README.md) | Learn the history underlying this field | [Lesson](1-Introduction/2-history-of-ML/README.md) | Jen and Amy |
| 03 | Fairness and machine learning | [Introduction](1-Introduction/README.md) | What are the important philosophical issues around fairness that students should consider when building and applying ML models? | [Lesson](1-Introduction/3-fairness/README.md) | Tomomi |
| 03 | Fairness and machine learning | [Introduction](1-Introduction/README.md) | What are the important philosophical issues around fairness that students should consider when building and applying ML models? | [Lesson](1-Introduction/3-fairness/README.md) | Tomomi |
@ -88,9 +90,9 @@ By ensuring that the content aligns with projects, the process is made more enga
| 07 | North American pumpkin prices 🎃 | [Regression](2-Regression/README.md) | Build linear and polynomial regression models | <ul><li>[Python](2-Regression/3-Linear/README.md)</li><li>[R](2-Regression/3-Linear/solution/R/lesson_3-R.ipynb)</li></ul> | <ul><li>Jen</li><li>Eric Wanjau</li></ul> |
| 07 | North American pumpkin prices 🎃 | [Regression](2-Regression/README.md) | Build linear and polynomial regression models | <ul><li>[Python](2-Regression/3-Linear/README.md)</li><li>[R](2-Regression/3-Linear/solution/R/lesson_3-R.ipynb)</li></ul> | <ul><li>Jen</li><li>Eric Wanjau</li></ul> |
| 08 | North American pumpkin prices 🎃 | [Regression](2-Regression/README.md) | Build a logistic regression model | <ul><li>[Python](2-Regression/4-Logistic/README.md) </li><li>[R](2-Regression/4-Logistic/solution/R/lesson_4-R.ipynb)</li></ul> | <ul><li>Jen</li><li>Eric Wanjau</li></ul> |
| 08 | North American pumpkin prices 🎃 | [Regression](2-Regression/README.md) | Build a logistic regression model | <ul><li>[Python](2-Regression/4-Logistic/README.md) </li><li>[R](2-Regression/4-Logistic/solution/R/lesson_4-R.ipynb)</li></ul> | <ul><li>Jen</li><li>Eric Wanjau</li></ul> |
| 09 | A Web App 🔌 | [Web App](3-Web-App/README.md) | Build a web app to use your trained model | [Python](3-Web-App/1-Web-App/README.md) | Jen |
| 09 | A Web App 🔌 | [Web App](3-Web-App/README.md) | Build a web app to use your trained model | [Python](3-Web-App/1-Web-App/README.md) | Jen |
| 10 | Introduction to classification | [Classification](4-Classification/README.md) | Clean, prep, and visualize your data; introduction to classification |<ul><li> [Python](4-Classification/1-Introduction/README.md) </li><li>[R](4-Classification/1-Introduction/solution/R/lesson_10-R.ipynb) | <ul><li>Jen and Cassie</li><li>Eric Wanjau</li></ul> |
| 10 | Introduction to classification| [Classification](4-Classification/README.md) | Clean, prep, and visualize your data; introduction to classification |<ul><li> [Python](4-Classification/1-Introduction/README.md) </li><li>[R](4-Classification/1-Introduction/solution/R/lesson_10-R.ipynb) | <ul><li>Jen and Cassie</li><li>Eric Wanjau</li></ul> |
| 11 | Delicious Asian and Indian cuisines 🍜 | [Classification](4-Classification/README.md) | Introduction to classifiers |<ul><li> [Python](4-Classification/2-Classifiers-1/README.md)</li><li>[R](4-Classification/2-Classifiers-1/solution/R/lesson_11-R.ipynb) | <ul><li>Jen and Cassie</li><li>Eric Wanjau</li></ul> |
| 11 | Delicious Asian and Indian cuisines 🍜| [Classification](4-Classification/README.md) | Introduction to classifiers |<ul><li> [Python](4-Classification/2-Classifiers-1/README.md)</li><li>[R](4-Classification/2-Classifiers-1/solution/R/lesson_11-R.ipynb) | <ul><li>Jen and Cassie</li><li>Eric Wanjau</li></ul> |
| 12 | Delicious Asian and Indian cuisines 🍜 | [Classification](4-Classification/README.md) | More classifiers |<ul><li>[Python](4-Classification/3-Classifiers-2/README.md)</li><li>[R](4-Classification/3-Classifiers-2/solution/R/lesson_12-R.ipynb) | <ul><li>Jen and Cassie</li><li>Eric Wanjau</li></ul> |
| 12 | Delicious Asian and Indian cuisines 🍜 |[Classification](4-Classification/README.md) | More classifiers |<ul><li> [Python](4-Classification/3-Classifiers-2/README.md)</li><li>[R](4-Classification/3-Classifiers-2/solution/R/lesson_12-R.ipynb) | <ul><li>Jen and Cassie</li><li>Eric Wanjau</li></ul> |
| 13 | Delicious Asian and Indian cuisines 🍜 | [Classification](4-Classification/README.md) | Build a recommender web app using your model | [Python](4-Classification/4-Applied/README.md) | Jen |
| 13 | Delicious Asian and Indian cuisines 🍜 | [Classification](4-Classification/README.md) | Build a recommender web app using your model | [Python](4-Classification/4-Applied/README.md) | Jen |
| 14 | Introduction to clustering | [Clustering](5-Clustering/README.md) | Clean, prep, and visualize your data; Introduction to clustering | <ul><li> [Python](5-Clustering/1-Visualize/README.md)</li><li>[R](5-Clustering/1-Visualize/solution/R/lesson_14-R.ipynb) | <ul><li>Jen</li><li>Eric Wanjau</li></ul> |
| 14 | Introduction to clustering | [Clustering](5-Clustering/README.md) | Clean, prep, and visualize your data; Introduction to clustering | <ul><li> [Python](5-Clustering/1-Visualize/README.md)</li><li>[R](5-Clustering/1-Visualize/solution/R/lesson_14-R.ipynb) | <ul><li>Jen</li><li>Eric Wanjau</li></ul> |
Mohit Jaisal
3 years ago
committed by
GitHub
