A curated list of awesome Deep Learning tutorials, projects and communities.
Free Online Books
- Deep Learning by Yoshua Bengio, Ian Goodfellow and Aaron Courville (01/01/2015)
- Neural Networks and Deep Learning by Michael Nielsen (Dec 2014)
- Deep Learning by Microsoft Research (2013)
- Deep Learning Tutorial by LISA lab, University of Montreal (Jan 6 2015)
Courses
- Machine Learning - Stanford by Andrew Ng in Coursera (2010-2014)
- Machine Learning - Caltech by Yaser Abu-Mostafa (2012-2014)
- Machine Learning - Carnegie Mellon by Tom Mitchell (Spring 2011)
- Neural Networks for Machine Learning by Geoffrey Hinton in Coursera (2012)
- Neural networks class by Hugo Larochelle from Université de Sherbrooke (2013)
- Deep Learning Course by CILVR lab @ NYU (2014)
- A.I - Berkeley by Dan Klein and Pieter Abbeel (2013)
- A.I - MIT by Patrick Henry Winston (2010)
- Vision and learning - computers and brains by Shimon Ullman, Tomaso Poggio, Ethan Meyers @ MIT (2013)
Video and Lectures
- How To Create A Mind By Ray Kurzweil
- Deep Learning, Self-Taught Learning and Unsupervised Feature Learning By Andrew Ng
- Recent Developments in Deep Learning By Geoff Hinton
- The Unreasonable Effectiveness of Deep Learning by Yann LeCun
- Deep Learning of Representations by Yoshua bengio
- Principles of Hierarchical Temporal Memory by Jeff Hawkins
- Machine Learning Discussion Group - Deep Learning w/ Stanford AI Lab by Adam Coates
- Making Sense of the World with Deep Learning By Adam Coates
- Demystifying Unsupervised Feature Learning By Adam Coates
- Visual Perception with Deep Learning By Yann LeCun
- The Next Generation of Neural Networks By Geoffrey Hinton at GoogleTechTalks
- The wonderful and terrifying implications of computers that can learn By Jeremy Howard at TEDxBrussels
Papers
- ImageNet Classification with Deep Convolutional Neural Networks
- Using Very Deep Autoencoders for Content Based Image Retrieval
- Learning Deep Architectures for AI
- CMU’s list of papers
Tutorials
- UFLDL Tutorial 1
- UFLDL Tutorial 2
- Deep Learning for NLP (without Magic)
- A Deep Learning Tutorial: From Perceptrons to Deep Networks
- Deep Learning from the Bottom up
WebSites
Datasets
- MNIST Handwritten digits
- Google House Numbers from street view
- CIFAR-10 and CIFAR-1004.
- IMAGENET
- Tiny Images 80 Million tiny images6.
- Flickr Data 100 Million Yahoo dataset
- Berkeley Segmentation Dataset 500
Frameworks
Miscellaneous
- Google Plus - Deep Learning Community
- Caffe Webinar
- 100 Best Github Resources in Github for DL
- Word2Vec
- Caffe DockerFile
- TorontoDeepLEarning convnet
- Vision data sets
- Fantastic Torch Tutorial
- gfx.js
- Torch7 Cheat sheet
- Misc from MIT’s ‘Advanced Natural Language Processing’ course
- Misc from MIT’s ‘Machine Learning’ course
- Misc from MIT’s ‘Networks for Learning: Regression and Classification’ course
- Misc from MIT’s ‘Neural Coding and Perception of Sound’ course
- Implementing a Distributed Deep Learning Network over Spark
Contributing
Have anything in mind that you think is awesome and would fit in this list? Feel free to send a pull request.