Skip to content

Teaching materials for the machine learning and deep learning classes at Stanford and Cornell

Notifications You must be signed in to change notification settings

kuleshov/teaching-material

Folders and files

NameName
Last commit message
Last commit date

Latest commit

 

History

38 Commits
 
 
 
 
 
 

Repository files navigation

Tutorials for Machine Learning Courses at Stanford and Cornell

Preparatory material for machine learning courses at Stanford at Cornell. Covers Python and Numpy. This has been used for:

  • The probabilistic graphical models and the deep learning courses at Stanford.
  • The applied machine learning course and deep generative models courses at Cornell.

Material

This repo currently holds:

  • A tutorial on basic Python/Numpy that is necesseary to get started with the above machine learning classes.

You may follow the iPython notebook on github, or clone and execute it locally. The notebook is based on an earlier version prepared by Justin Johnson.

About

Teaching materials for the machine learning and deep learning classes at Stanford and Cornell

Resources

Stars

Watchers

Forks

Releases

No releases published

Packages

No packages published