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Artificial Neural Networks and Data Analysis

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If you have a question about this talk, please contact Dr Matteo Bianconi.

Extracting the dimension of the data set. Choosing the number of input and output neurons. Definition of the architecture of the ANN , layers, weights and transfer functions. Definition of patterns, pattern recognition, retrieval and forecast. Definition of the learning and the generalization error. Capacity of the neural networks. Critical Capacity. Learning procedure, retrieve and recognition. Monte Carlo Method and Steepest Descent.

This talk is part of the Astrophysics Seminars series.

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