This project follows UFLDL tutorial of Stanford University. Some useful materials on the web : http://ufldl.stanford.edu/wiki/index.php/UFLDL_Tutorial All sub-branches below should be implemented 1.Sparse Autoencoder 2.Vectorizd implementation 3.Preprocessing:PCA and Whitening 4.Softmax Regression 5.Self-Taught Learning and Unsupervised Feather Learning 6.Building Deep Networks for Classification 7.Linear Decoders with Autoencoders 8.Working with Large Images
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This project includes how to implement sparse autoEncoder, Vectorization, and so on.
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