【深度学习精选系列】很棒的深度学习

精心策划的深度学习教程、项目和社区列表。

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. 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)
10. Convolutional Neural Networks for Visual Recognition - Stanford by Fei-Fei Li, Andrej Karpathy (2017)
11. Deep Learning for Natural Language Processing - Stanford
12. Neural Networks - usherbrooke
13. Machine Learning - Oxford (2014-2015)
14. Deep Learning - Nvidia (2015)
15. Graduate Summer School: Deep Learning, Feature Learning by Geoffrey Hinton, Yoshua Bengio, Yann LeCun, Andrew Ng, Nando de Freitas and several others @ IPAM, UCLA (2012)
16. Deep Learning - Udacity/Google by Vincent Vanhoucke and Arpan Chakraborty (2016)
17. Deep Learning - UWaterloo by Prof. Ali Ghodsi at University of Waterloo (2015)
18. Statistical Machine Learning - CMU by Prof. Larry Wasserman
19. Deep Learning Course by Yann LeCun (2016)
20. Designing, Visualizing and Understanding Deep Neural Networks-UC Berkeley
21. UVA Deep Learning Course MSc in Artificial Intelligence for the University of Amsterdam.
22. MIT 6.S094: Deep Learning for Self-Driving Cars
23. MIT 6.S191: Introduction to Deep Learning