# Deep learning Reading List

Following is a growing list of some of the materials i found on the web for Deep Learning beginners.

### Free Online Books

- Deep Learning by Yoshua Bengio, Ian Goodfellow and Aaron Courville
- Neural Networks and Deep Learning by Michael Nielsen
- Deep Learning by Microsoft Research
- Deep Learning Tutorial by LISA lab, University of Montreal

### Courses

- Machine Learning by Andrew Ng in Coursera
- Neural Networks for Machine Learning by Geoffrey Hinton in Coursera
- Neural networks class by Hugo Larochelle from Université de Sherbrooke
- Deep Learning Course by CILVR lab @ NYU
- CS231n: Convolutional Neural Networks for Visual Recognition On-Going
- CS224d: Deep Learning for Natural Language Processing Going to start

### Video and Lectures

- How To Create A Mind By Ray Kurzweil - Is a inspiring talk
- 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

### 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

### WebSites

### Datasets

- MNIST Handwritten digits
- Google House Numbers from street view
- CIFAR-10 and CIFAR-100
- IMAGENET
- Tiny Images 80 Million tiny images
- Flickr Data 100 Million Yahoo dataset
- Berkeley Segmentation Dataset 500