Machine Learning + Deep Learning + Computer Vision + Natural Language Processing: Principles, Practices and Applications --- Dry Goods Sharing (Continuously updated...)

• Stanford c231n (Youtube)　××××××
• Google Deep Learning Course on Udacity
  
• [Coursera] Neural Networks for Machine Learning — Geoffrey Hinton 2016
  
• Neural networks class - University of Sherbrooke
  
• MIT 6.S094: Introduction to Deep Learning and Self-Driving Car
  
• Oxford Machine Learning: 2014-2015
• MIT 6.034 Artificial Intelligence, Fall 2010
• NVIDIA Deep Learning Course
• Practical Deep Learning for Coders
• Deep Learning and Neural Networks (John Hopkins Univ)

Deep Learning Resource from DL4J

A collection of NIPS 2016 Tutorials

Good Blogs:

• http://pinouchon.github.io/
  
• https://adeshpande3.github.io/
• https://yjango.gitbooks.io/superorganism/
  
• Agustinus Kristiadi's Blog (collection of GAN networks explanation and implementation)
  
• http://kexue.fm/
  

David Silver Reinforcement Learning Open Class: 

1. Getting Started with Reinforcement Learning
   
2. Markov Decision Process MDP
   
3. Dynamic programming to solve the Planning problem of MDP
   
4. Model-Free Learning (solve the Prediction problem under the unknown Environment)
   
5. Model-Free Control (solve the Control problem under unknown Environment)
   
6. Solve the approximate value function
   
7. Policy Gradient
   
8. Integrating Learning and Planning (modeling the Environment)
   
9. Explore and utilize
   

GAN paper collection：

1. GAN papers
   

Chat Bot

1. Do-it-yourself chatbot
   

https://tulongf.github.io

http://www.wildml.com/

Tutorial Slides by Andrew Moore   Tutorial Slides by Andrew Moore

machinelearningmastery.com

gloqo.com  (deep learning git code repo collection)