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| :-----------: | :--------------------------------------: | :----------------------------------: | ---------------------------------------------------------------------------------------------------- | :------------------------------------------------: | :-------: |
| 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 | Introduction to Regression | [Regression](2-Regression/README.md) | Get started with Python and Scikit-Learn for Regression models | [lesson](2-Regression/1-Tools/README.md) | Jen |
| 03 | Introduction to Regression | [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 |
| 05 | North American Pumpkin Prices 🎃 | [Regression](2-Regression/README.md) | Build Linear and Polynomial Regression models | [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 |
| 07 | Introduction to Clustering | [Clustering]() | tbd | [lesson]() | Cassie |
| 08 | Delicious Asian Recipes 🍜 | [Clustering]() | tbd | [lesson]() | Cassie |
| 09 | Delicious Asian Recipes 🍜 | [Clustering]() | tbd | [lesson]() | Cassie |
| 10 | Delicious Asian Recipes 🍜 | [Clustering]() | tbd | [lesson]() | Cassie |
| 11 | Introduction to Classification | [Classification]() | | [lesson]() | Paige |
| 12 | Interesting Maya Architecture 🦜 | [Classification]() | | [lesson]() | Paige |
| 13 | Interesting Maya Architecture 🦜 | [Classification]() | | [lesson]() | Paige |
| 14 | Interesting Maya Architecture 🦜 | [Classification]() | | [lesson]() | Paige |
| 15 | Introduction to NLP | [Natural Language Processing]() | tbd | [lesson]() | Stephen |
| 16 | Romantic Hotels of Europe ♥️ | [Natural Language Processing]() | tbd | [lesson]() | Stephen |
| 07 | Introduction to Clustering | [Clustering]() | tbd | [lesson]() | Cassie |
| 08 | Delicious Asian Recipes 🍜 | [Clustering]() | tbd | [lesson]() | Cassie |
| 09 | Delicious Asian Recipes 🍜 | [Clustering]() | tbd | [lesson]() | Cassie |
| 10 | Delicious Asian Recipes 🍜 | [Clustering]() | tbd | [lesson]() | Cassie |
| 11 | Introduction to Classification | [Classification]() | | [lesson]() | Paige |
| 12 | Interesting Maya Architecture 🦜 | [Classification]() | | [lesson]() | Paige |
| 13 | Interesting Maya Architecture 🦜 | [Classification]() | | [lesson]() | Paige |
| 14 | Interesting Maya Architecture 🦜 | [Classification]() | | [lesson]() | Paige |
| 15 | Introduction to NLP | [Natural Language Processing]() | tbd | [lesson]() | Stephen |
| 16 | Romantic Hotels of Europe ♥️ | [Natural Language Processing]() | tbd | [lesson]() | Stephen |
| 17 | Romantic Hotels of Europe ♥️ | [Natural Language Processing]() | tbd | [lesson]() | Stephen |
| 18 | Romantic Hotels of Europe ♥️ | [Natural Language Processing]() | tbd | [lesson]() | Stephen |
| 19 | Introduction to Time Series Forecasting | [Time Series]() | tbd | [lesson]() | Francesca |
| 19 | Introduction to Time Series Forecasting | [Time Series]() | tbd | [lesson]() | Francesca |
| 20 | Power Usage in India ⚡️ | [Time Series]() | tbd | [lesson]() | Francesca |
| 21 | Introduction to Reinforcement Learning | [Reinforcement Learning]() | tbd | [lesson]() | Dmitry |
| 22 | A fancy French mousetrap 🍫 | [Reinforcement Learning]() | tbd | [lesson]() | Dmitry |
| 21 | Introduction to Reinforcement Learning | [Reinforcement Learning]() | tbd | [lesson]() | Dmitry |
| 22 | A fancy French mousetrap 🍫 | [Reinforcement Learning]() | tbd | [lesson]() | Dmitry |
| 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) | Tomomi |
| 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) | All |
| 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) | All |
## Offline access
You can run this documentation offline by using [Docsify](https://docsify.js.org/#/). Fork this repo, [install Docsify](https://docsify.js.org/#/quickstart) on your local machine, and then in the root folder of this repo, type `docsify serve`. The website will be served on port 3000 on your localhost: `localhost:3000`.

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