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PyBrain already includes a function that does just that, gradientCheck(). You can pass it to any network containing a structural component that you have programmed. It will check if the numeric gradients are (roughly) equal to the gradient specified by the _backwardImplementation() methods.
PyBrain stands for Python-Based Reinforcement Learning, Artificial Intelligence, and Neural Networks Library. It is a modular machine learning library n python that contains very powerful and easy-to-use algorithms used to aid in a variety of machine learning tasks.
I am trying to use PyBrain for some simple NN training. What I don't know how to do is to load the training data from a file. It is not explained in their website anywhere. I don't care about the format because I can build it now, but I need to do it in a file instead of adding row by row manually, because I will have several hundreds of rows.
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