/awesome-deep-learning

A curated list of awesome Deep Learning tutorials, projects and communities.

Free Online Books

  1. Deep Learning by Yoshua Bengio, Ian Goodfellow and Aaron Courville (01/01/2015)
  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)neuraltalk by Andrej Karpathy : numpy-based RNN/LSTM implementation
  5. An introduction to genetic algorithms
  6. Artificial Intelligence: A Modern Approach
  7. Deep Learning in Neural Networks: An Overview

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 (2015)
  11. Deep Learning for Natural Language Processing - Stanford
  12. Neural Networks - usherbrooke
  13. Machine Learning - Oxford (2014-2015)
  14. Deep Learning - Nvidia (2015)

Videos and Lectures

  1. How To Create A Mind By Ray Kurzweil
  2. Deep Learning, Self-Taught Learning and Unsupervised Feature Learning By Andrew Ng
  3. Recent Developments in Deep Learning By Geoff Hinton
  4. The Unreasonable Effectiveness of Deep Learning by Yann LeCun
  5. Deep Learning of Representations by Yoshua bengio
  6. Principles of Hierarchical Temporal Memory by Jeff Hawkins
  7. Machine Learning Discussion Group - Deep Learning w/ Stanford AI Lab by Adam Coates
  8. Making Sense of the World with Deep Learning By Adam Coates
  9. Demystifying Unsupervised Feature Learning By Adam Coates
  10. Visual Perception with Deep Learning By Yann LeCun
  11. The Next Generation of Neural Networks By Geoffrey Hinton at GoogleTechTalks
  12. The wonderful and terrifying implications of computers that can learn By Jeremy Howard at TEDxBrussels
  13. Unsupervised Deep Learning - Stanford by Andrew Ng in Stanford (2011)
  14. [Natural Language Processing] (http://web.stanford.edu/class/cs224n/handouts/) By Chris Manning in Stanford

Papers

  1. ImageNet Classification with Deep Convolutional Neural Networks
  2. Using Very Deep Autoencoders for Content Based Image Retrieval
  3. Learning Deep Architectures for AI
  4. CMU’s list of papers
  5. Neural Networks for Named Entity Recognition zip
  6. Training tricks by YB
  7. [Geoff Hinton's reading list (all papers)] (http://www.cs.toronto.edu/~hinton/deeprefs.html)
  8. Supervised Sequence Labelling with Recurrent Neural Networks
  9. Statistical Language Models based on Neural Networks
  10. Training Recurrent Neural Networks
  11. Recursive Deep Learning for Natural Language Processing and Computer Vision
  12. Bi-directional RNN
  13. LSTM
  14. GRU - Gated Recurrent Unit
  15. GFRNN . .
  16. LSTM: A Search Space Odyssey
  17. A Critical Review of Recurrent Neural Networks for Sequence Learning
  18. Visualizing and Understanding Recurrent Networks
  19. Wojciech Zaremba, Ilya Sutskever, An Empirical Exploration of Recurrent Network Architectures
  20. Recurrent Neural Network based Language Model
  21. Extensions of Recurrent Neural Network Language Model
  22. Recurrent Neural Network based Language Modeling in Meeting Recognition
  23. Deep Neural Networks for Acoustic Modeling in Speech Recognition
  24. Speech Recognition with Deep Recurrent Neural Networks
  25. Reinforcement Learning Neural Turing Machines
  26. Learning Phrase Representations using RNN Encoder-Decoder for Statistical Machine Translation
  27. Google - Sequence to Sequence Learning with Nneural Networks
  28. Memory Networks
  29. Policy Learning with Continuous Memory States for Partially Observed Robotic Control
  30. Microsoft - Jointly Modeling Embedding and Translation to Bridge Video and Language
  31. Neural Turing Machines

Tutorials

  1. UFLDL Tutorial 1
  2. UFLDL Tutorial 2
  3. Deep Learning for NLP (without Magic)
  4. A Deep Learning Tutorial: From Perceptrons to Deep Networks
  5. Deep Learning from the Bottom up
  6. Theano Tutorial
  7. Neural Networks for Matlab
  8. Using convolutional neural nets to detect facial keypoints tutorial
  9. Torch7 Tutorials
  10. [The Best Machine Learning Tutorials On The Web] (https://github.com/josephmisiti/machine-learning-module)

WebSites

  1. deeplearning.net
  2. deeplearning.stanford.edu
  3. nlp.stanford.edu
  4. ai-junkie.com
  5. cs.brown.edu/research/ai
  6. eecs.umich.edu/ai
  7. cs.utexas.edu/users/ai-lab
  8. cs.washington.edu/research/ai
  9. aiai.ed.ac.uk
  10. www-aig.jpl.nasa.gov
  11. csail.mit.edu
  12. cgi.cse.unsw.edu.au/~aishare
  13. cs.rochester.edu/research/ai
  14. ai.sri.com
  15. isi.edu/AI/isd.htm
  16. nrl.navy.mil/itd/aic
  17. hips.seas.harvard.edu
  18. AI Weekly
  19. stat.ucla.edu
  20. deeplearning.cs.toronto.edu
  21. jeffdonahue.com/lrcn/
  22. visualqa.org
  23. www.mpi-inf.mpg.de/departments/computer-vision...

Datasets

  1. MNIST Handwritten digits
  2. Google House Numbers from street view
  3. CIFAR-10 and CIFAR-1004.
  4. IMAGENET
  5. Tiny Images 80 Million tiny images6.
  6. Flickr Data 100 Million Yahoo dataset
  7. Berkeley Segmentation Dataset 500
  8. UC Irvine Machine Learning Repository
  9. Flickr 8k
  10. Flickr 30k
  11. Microsoft COCO
  12. VQA
  13. Image QA

Frameworks

  1. Caffe
  2. Torch7
  3. Theano
  4. cuda-convnet
  5. convetjs
  6. Ccv
  7. NuPIC
  8. DeepLearning4J
  9. Brain
  10. DeepLearnToolbox
  11. Deepnet
  12. Deeppy
  13. JavaNN
  14. hebel
  15. Mocha.jl
  16. OpenDL
  17. cuDNN
  18. MGL
  19. KUnet.jl
  20. Nvidia DIGITS - a web app based on Caffe
  21. Neon - Python based Deep Learning Framework
  22. Keras - Theano based Deep Learning Library
  23. Chainer - A flexible framework of neural networks for deep learning
  24. RNNLM Toolkit
  25. RNNLIB - A recurrent neural network library

Miscellaneous

  1. Google Plus - Deep Learning Community
  2. Caffe Webinar
  3. 100 Best Github Resources in Github for DL
  4. Word2Vec
  5. Caffe DockerFile
  6. TorontoDeepLEarning convnet
  7. Vision data sets
  8. gfx.js
  9. Torch7 Cheat sheet
  10. [Misc from MIT's 'Advanced Natural Language Processing' course] (http://ocw.mit.edu/courses/electrical-engineering-and-computer-science/6-864-advanced-natural-language-processing-fall-2005/)
  11. Misc from MIT's 'Machine Learning' course
  12. Misc from MIT's 'Networks for Learning: Regression and Classification' course
  13. Misc from MIT's 'Neural Coding and Perception of Sound' course
  14. Implementing a Distributed Deep Learning Network over Spark
  15. A chess AI that learns to play chess using deep learning.
  16. [Reproducing the results of "Playing Atari with Deep Reinforcement Learning" by DeepMind] (https://github.com/kristjankorjus/Replicating-DeepMind)
  17. Wiki2Vec. Getting Word2vec vectors for entities and word from Wikipedia Dumps
  18. The original code from the DeepMind article + tweaks
  19. Google deepdream - Neural Network art
  20. An efficient, batched LSTM.

Contributing

Have anything in mind that you think is awesome and would fit in this list? Feel free to send a pull request.

License

CC0

To the extent possible under law, Christos Christofidis has waived all copyright and related or neighboring rights to this work.