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This is an implementation of two machine learning algorithms, Contrastive Divergence and Back-propagation. Contrastive Divergence is used to pre-train each layer of the Neural Network as a Restricted Boltzmann Machine. After the RBM training the weights should approximate the problem space represented by the dataset. Back-propagation is then used to classify the data.
