By Jeff Heaton
Creation to Neural Networks with C#, moment version, introduces the C# programmer to the area of Neural Networks and synthetic Intelligence. Neural community architectures, equivalent to the feedforward, Hopfield, and self-organizing map architectures are mentioned. education innovations, similar to backpropagation, genetic algorithms and simulated annealing also are brought. useful examples are given for every neural community. Examples comprise the touring salesman challenge, handwriting reputation, monetary prediction, video game process, mathematical services, and net bots. All C# resource code is accessible on-line for simple downloading.
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Additional info for Introduction to Neural Networks for C#, 2nd Edition
1: A typical matrix. 398 XXXIII XXXIV Introduction to Neural Networks for C#, Second Edition Introduction Introduction This book provides an introduction to neural network programming using C#. It focuses on the feedforward neural network, but also covers Hopfield neural networks, as well as self-organizing maps. Chapter 1 provides an overview of neural networks. You will be introduced to the mathematical underpinnings of neural networks and how to calculate their values manually. You will also see how neural networks use weights and thresholds to determine their output.
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