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I have been doing work on Theano based autoencoder. For data size of less than 100, it is working perfectly using batch gradient descent. But for data size around 500, it is better to use mini batch gradient descent I think. Because it takes long time for training. So, What is the minimum number of samples required for mini batch gradient descent ? Any suggestions about mini batch size also ? The error is less for batch gradient descent than mini batch gradients (mini_batch_size :25, n_epochs : 200).