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Using the tools of complexity theory, Stephen Judd develops a formal description of associative learning in connectionist networks. He rigorously exposes the co
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Neural networks usually work adequately on small problems but can run into trouble when they are scaled up to problems involving large amounts of input data. Ci
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Deep Learning Neural Networks: Design And Case Studies
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Deep Learning Neural Networks is the fastest growing field in machine learning. It serves as a powerful computational tool for solving prediction, decision, dia
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Artificial neural networks and genetic algorithms both are areas of research which have their origins in mathematical models constructed in order to gain unders