Neural Network Learning and Expert Systems presents a unified and in-depth development of neural network learning algorithms and neural network expert systems. Especially suitable for students and researchers in computer science, engineering, and psychology, it provides a systematic development of neural network learning algorithms from a computational perspective. This is...
Prentice-Hall, 1997. — 640 p. Neuro-Fuzzy Modeling and Soft Computing places particular emphasis on the theoretical aspects of covered methodologies, as well as empirical observations and verifications of various applications in practice. Neuro-Fuzzy Modeling and Soft Computing is oriented toward methodologies that are likely to be of practical use. It includes exercises, some...
Apress, 2018. — 425 p. — ISBN: 1484237897. Code files only! Work with advanced topics in deep learning, such as optimization algorithms, hyper-parameter tuning, dropout, and error analysis as well as strategies to address typical problems encountered when training deep neural networks. You’ll begin by studying the activation functions mostly with a single neuron (ReLu, sigmoid,...
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