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Machine Learning cheatsheets for Stanford's CS 229
Available in العربية - English - Español - فارسی - Français - 한국어 - Português - Türkçe - Tiếng Việt - 简中 - 繁中
Goal
This repository aims at summing up in the same place all the important notions that are covered in Stanford's CS 229 Machine Learning course, and include:
- Refreshers in related topics that highlight the key points of the prerequisites of the course.
- Cheatsheets for each machine learning field, as well as another dedicated to tips and tricks to have in mind when training a model.
- All elements of the above combined in an ultimate compilation of concepts, to have with you at all times!
Content
VIP Cheatsheets
 |  |  |  |
|---|---|---|---|
| Supervised Learning | Unsupervised Learning | Deep Learning | Tips and tricks |
VIP Refreshers
 |  |
|---|---|
| Probabilities and Statistics | Algebra and Calculus |
Super VIP Cheatsheet
 |
|---|
| All the above gathered in one place |
Website
This material is also available on a dedicated website, so that you can enjoy reading it from any device.