IFT6266 – Deep Learning: Resources

IFT6266 – Deep Learning: Resources

I’m currently taking IFT6266 Grad Course at UdeM (Winter 2017) and as part of the class, we have to maintain a blog.

I’m a little late with mine, but I’m catching up, so there will be quite a bit of activity in the coming weeks!

In the meantime, here is a nice list of resources to get started with Deep Learning.

 

Papers

No need to make a list, there is an “awesome” list here: 
https://github.com/terryum/awesome-deep-learning-papers

 

Courses

 

Resources

Awesome list of resources here as well.

 

Books

  • Deep Learning Book (Ian Goodfellow, Yoshua Bengio, Aaron Courville)
  • http://shop.oreilly.com/product/0636920052289.do

 

Datasets

Most of Deep Learning frameworks include them and/or include functions to load them.

 

Awesome People to Follow

Siraj Raval – Youtube. Posting “hands on stuff” weekly!

Andrej Karpathy – PhD from Stanford (under Fei-Fei Li)

Alex Graves, Ilya Sutskever and Tomas Mikolov

Colah’s blog

Richard Socher

 

Other Cool Stuff

http://cs.stanford.edu/people/karpathy/convnetjs/

http://www.r2d3.us/

https://clarifai.com/demo

https://nlp.stanford.edu/sentiment/treebank.html

Neural Photo Editor

 

 


This post is part of the IFT6266 Blog Post Series.
You will find most of the code in the corresponding GitHub here.