This project directs you to good resources to learn Machine Learning, Deep Learning and Reinforcement Learning.The content of this page is mainly collected from the web, especially from Quora website.
If you are beginner to ML, start with Andrew Ng class on Machine Learning https://www.coursera.org/learn/machine-learning
Deep Learning at Oxford 2015: https://www.youtube.com/playlist?list=PLE6Wd9FR--EfW8dtjAuPoTuPcqmOV53Fu&app=desktop
Nueral Networks for Machine Learning(without certificate): https://www.coursera.org/learn/neural-networks
Nueral Network class: http://info.usherbrooke.ca/hlarochelle/neural_networks/content.html
Need more theory? : https://work.caltech.edu/telecourse.html
Neural Networks and Deep Learning Book: http://neuralnetworksanddeeplearning.com/
Deep Learning Book: http://www.deeplearningbook.org/ https://webdocs.cs.ualberta.ca/~sutton/book/ebook/the-book.html
more research: https://deepmind.com/research/publications/
Computer Vision: http://cs231n.github.io/ also check: https://sites.google.com/site/mostafasibrahim/research/articles/how-to-start
Natural Language Processing (NLP): get started: http://web.stanford.edu/class/cs224n/ with latest researches: http://cs224d.stanford.edu/ know more: https://www.quora.com/How-do-I-learn-Natural-Language-Processing/answer/Vivek-Kumar-893
Memory Network: https://arxiv.org/abs/1410.3916 https://arxiv.org/abs/1506.07285
Deep Reinforcement Learning: Introduction: http://colah.github.io/posts/2015-08-Understanding-LSTMs/ http://karpathy.github.io/2015/05/21/rnn-effectiveness/
http://www0.cs.ucl.ac.uk/staff/d.silver/web/Teaching.html
https://webdocs.cs.ualberta.ca/~sutton/book/ebook/the-book.html
Generative Models: https://arxiv.org/abs/1406.2661 https://arxiv.org/abs/1312.6114 https://arxiv.org/abs/1601.06759
https://arxiv.org/abs/1406.2661
https://arxiv.org/abs/1511.06434
https://github.com/Newmu/dcgan_code
https://github.com/david-gpu/srez
start with classifying the MNIST dataset: http://yann.lecun.com/exdb/mnist/
Try face detection and classification on ImageNet: http://image-net.org/index
Do a Twitter sentiment analysis using RNNs:https://cs224d.stanford.edu/reports/YuanYe.pdf or
CNNs:http://casa.disi.unitn.it/~moschitt/since2013/2015_SIGIR_Severyn_TwitterSentimentAnalysis.pdf
Teach neural networks to reproduce the artistic style of famous painters:https://arxiv.org/abs/1508.06576v1
Compose Music With Recurrent Neural Networks:http://www.hexahedria.com/2015/08/03/composing-music-with-recurrent-neural-networks/
Play ping-pong using Deep Reinforcement Learning:http://karpathy.github.io/2016/05/31/rl/
Neural Networks to Rate a selfie:http://karpathy.github.io/2015/10/25/selfie/
Automatically color Black & White pictures using Deep Learning:https://twitter.com/ColorizeBot
https://christopherolah.wordpress.com/