-> This is a solution to the Sparse Autoencoder exercise in the Stanford UFLDL Tutorial(http://ufldl.stanford.edu/wiki/index.php/Exercise:Sparse_Autoencoder) -> The code has been written in Python using Scipy, Numpy and Matplotlib -> The code is bound by The MIT License (MIT) Running the code: -> Download the data file 'IMAGES.mat' and the code file 'sparseAutoencoder.py' -> Put them in the same folder, and run the program by typing in 'python sparseAutoencoder.py' in the command line -> You should get an output similar to the file 'output.png' -> The code takes about one and a half minutes to execute on an i3 processor