# Awesome Deep Learning

Table of Contents

• Books

• Courses

• Videos and Lectures

• Papers

• Tutorials

• Researchers

• Websites

• Datasets

• Conferences

• Frameworks

• Tools

• Miscellaneous

• Contributing

Books

1. Deep Learning by Yoshua Bengio, Ian Goodfellow and Aaron Courville (05/07/2015)
2. Neural Networks and Deep Learning by Michael Nielsen (Dec 2014)
3. Deep Learning by Microsoft Research (2013)
4. Deep Learning Tutorial by LISA lab, University of Montreal (Jan 6 2015)
5. neuraltalk by Andrej Karpathy : numpy-based RNN/LSTM implementation
6. An introduction to genetic algorithms
7. Artificial Intelligence: A Modern Approach
8. Deep Learning in Neural Networks: An Overview
9. Artificial intelligence and machine learning: Topic wise explanation
10. Grokking Deep Learning for Computer Vision
11. Dive into Deep Learning - numpy based interactive Deep Learning book
12. Practical Deep Learning for Cloud, Mobile, and Edge - A book for optimization techniques during production.
13. Math and Architectures of Deep Learning - by Krishnendu Chaudhury
14. TensorFlow 2.0 in Action - by Thushan Ganegedara
15. Deep Learning for Natural Language Processing - by Stephan Raaijmakers
16. Deep Learning Patterns and Practices - by Andrew Ferlitsch
17. Inside Deep Learning - by Edward Raff
18. Deep Learning with Python, Second Edition - by François Chollet
19. Evolutionary Deep Learning - by Micheal Lanham
20. Engineering Deep Learning Platforms - by Chi Wang and Donald Szeto
21. Deep Learning with R, Second Edition - by François Chollet with Tomasz Kalinowski and J. J. Allaire
22. Regularization in Deep Learning - by Liu Peng
23. Jax in Action - by Grigory Sapunov
24. Hands-On Machine Learning with Scikit-Learn, Keras, and TensorFlow by Aurélien Géron | Oct 15, 2019

Courses

1. Machine Learning - Stanford by Andrew Ng in Coursera (2010-2014)
2. Machine Learning - Caltech by Yaser Abu-Mostafa (2012-2014)
3. Machine Learning - Carnegie Mellon by Tom Mitchell (Spring 2011)
4. Neural Networks for Machine Learning by Geoffrey Hinton in Coursera (2012)
5. Neural networks class by Hugo Larochelle from Université de Sherbrooke (2013)
6. Deep Learning Course by CILVR lab @ NYU (2014)
7. A.I - Berkeley by Dan Klein and Pieter Abbeel (2013)
8. A.I - MIT by Patrick Henry Winston (2010)
9. Vision and learning - computers and brains by Shimon Ullman, Tomaso Poggio, Ethan Meyers @ MIT (2013)