Machine Learning cheatsheets for Stanford's CS 229

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.

Authors

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