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.

Translation

Would you like to see these cheatsheets in your native language? You can help us translating them on this dedicated repo!

Authors

Afshine Amidi (Ecole Centrale Paris, MIT) and Shervine Amidi (Ecole Centrale Paris, Stanford University)