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I use numpy for matrices, and scipy.optimize package for the L-BFGS minimization algorithm.
Deep learning learns low and high-level features from large amounts of unlabeled data, improving classification on different, labeled, datasets. Deep learning can achieve an accuracy of 98% on the MNIST dataset.