Introduction First of all, let me tell you this is part of the Coursera Machine Learning course. Here I will show how to implement a Neural Network Backpropation in Octave. I know there are already several options to do this in a very high level (TensorFlow), just focusing on inputs and outputs, but I would like to understand all the matrix and statistical fundamentals to later be able to choose the right strategies in high level programs. Backpropagation algorithm is a guided learning algorithm, i.e., we need to traning the Neural Network with real outputs in order to obtain good predictions.



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