The home of my deep neural network

Backgroud

整理收集关于深度神经网络的相关项目资料，方便自己学习，持续更新。

Course Resource

1. Neural Networks for Machine Learning

   https://class.coursera.org/neuralnets-2012-001
   ---Geoffrey Hinton
   AMA Geoffrey Hinton, 07 Nov 2014

2. Neural networks class - Université de Sherbrooke

   https://www.youtube.com/playlist?list=PL6Xpj9I5qXYEcOhn7TqghAJ6NAPrNmUBH (Youtube.com)
   http://v.youku.com/v_show/id_XNzEyMDYxMTc2.html?f=22795577 (优酷)
   ---Hugo Larochelle

3. UFLDL( Unsupervised Feature Learning and Deep Learning) Tutorial

   http://deeplearning.stanford.edu/wiki/index.php/UFLDL_Tutorial
   Material contributed by: Andrew Ng, Jiquan Ngiam, Chuan Yu Foo, Yifan Mai, Caroline Suen

Project Resource

1. cuda-convnet

   High-performance C++/CUDA implementation of convolutional neuralnetworks
   https://code.google.com/p/cuda-convnet/
   --- Alex Krizhevsky

2. Torch7

   Torch7 is a scientific computing framework with wide support for
   machine learning algorithms. It is easy to use and provides a very
   efficient implementation, thanks to an easy and fast scripting
   language, LuaJIT, and an underlying C implementation.
   http://torch.ch/

3. Pylearn2

   Pylearn2 is a machine learning library. Most of its functionality is
   built on top of Theano. This means you can write Pylearn2 plugins (new
   models, algorithms, etc) using mathematical expressions, and Theano
   will optimize and stabilize those expressions for you, and compile
   them to a backend of your choice (CPU or GPU).
   http://deeplearning.net/software/pylearn2/index.html

Book Resource

1. Deep Learning Tutorials
   > http://www.deeplearning.net/tutorial/
   > http://www.iro.umontreal.ca/~bengioy/dlbook/