关于neural network的一些资料

Books/Tutorials

1. Neural Networks - A systematic introduction http://www.inf.fu-berlin.de/inst/ag-ki/rojas_home/pmwiki/pmwiki.php?n=Books.NeuralNetworksBook

2. http://deeplearning.net/

3. Learning deep architectures for AI http://www.iro.umontreal.ca/~lisa/publications2/index.php/publications/show/239

4. Information Theory, Inference and Learning Algorithms http://www.inference.phy.cam.ac.uk/mackay/itila/ 5.
Gaussian Processeshttp://www.gaussianprocess.org/

5. http://www.iro.umontreal.ca/~bengioy/papers/ftml_book.pdf

Code Examples

1. Ruslan Salakhutdinov

http://www.mit.edu/~rsalakhu/software.html

2. Deep Learning - How I did it? http://blog.kaggle.com/2012/11/01/deep-learning-how-i-did-it-merck-1st-place-interview/

3. Boltzmann Machine - Necker Cube Example http://www.cs.cf.ac.uk/Dave/JAVA/boltzman/Necker.html

4. Graphlab http://select.cs.cmu.edu/code/graphlab/pmf.html

5. Netflix Recommendations http://techblog.netflix.com/2012/04/netflix-recommendations-beyond-5-stars.html

6. Prof. Radford Neal http://www.cs.toronto.edu/~radford/software-online.html

7. Prof. David MacKay http://www.inference.phy.cam.ac.uk/mackay/itprnn/softwareN.html

Recognizing Cursive Handwriting

1. Alex Graves RNNLIB

http://sourceforge.net/apps/mediawiki/rnnl/index.php?title=Main_Page

Speech Recognition

1. Deep Neural Networks for Acoustic Modeling in Speech Recognition (Nov 2012)http://research.microsoft.com/pubs/171498/HintonDengYuEtAl-SPM2012.pdf

2. http://www.cslu.ogi.edu/tutordemos/nnet_training/tutorial.html (May
not include recent developments)

3. Use of RNNs in continuous speech recognition http://svr-www.eng.cam.ac.uk/~ajr/rnn4csr94/rnn4csr94.html

unsupervised learning:

http://ufldl.stanford.edu/wiki/index.php/UFLDL_Tutorial

Hinton的主页：http://www.cs.toronto.edu/~hinton/