Deep Learning Cheat Sheets

Shervine Amidi, graduate student at Stanford, and Afshine Amidi, of MIT and Uber – creators of a recent set of machine leanring cheat sheets – have just published a new set of deep learning cheat sheets. These “VIP cheat sheets” are based on the materials from Stanford’s CS 230 (Github repo with PDFs available here), and include topics such as:

Recurrent Neural Networks Convolutional Neural Networks Hyperparameter tuning Object recognition Regularization Tips and tricks … and much more

![](https://camo.githubusercontent.com/a8eece53345340906d07e01b29980b92ed8c2ad3/68747470733a2f2f7374616e666f72642e6564752f7e7368657276696e652f696d616765732f7669702d636865617473686565742d636f6e766f6c7574696f6e616c2d6e657572616c2d6e6574732e706e673f)

Links to individual cheat sheets are below:**