Finding Minima Algorithms
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The learning process in supervised learning consists of tuning the network parameters (weights and biases) until a certain cost function is minimized. Since the number of parameters is quite large (they can easily be into thousands), a robust minimization algorithm is needed. This chapter presents a number of minimization algorithms of different flavors, and emphasizes their advantages and disadvantages.