Given numerical training data, nonlinear networks (including neural nets) learn how to map N-dimensional input vectors into M-dimensional output vectors. This makes nonlinear networks an ideal solution to a number of problems including pattern recognition, function approximation, data mining, and e-mail spam filtering. The diagram illustrates how our optimization system can use nonlinear networks to boost your application!

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