Daniel Graupe – Principles of Artificial Neural Networks (2nd Ed.)
Daniel Graupe – Principles of Artificial Neural Networks (2nd Ed.)
Daniel Graupe – Principles of Artificial Neural Networks (2nd Ed.)
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Description
DANIEL GRAUPE – PRINCIPLES OF ARTIFICIAL NEURAL NETWORKS (2ND ED.)
Artificial neural networks can be used to solve problems that are complex, ill-defined and highly unpredictable. The basic theory and architecture of artificial neural networks are covered in this volume. It presents 18 complete case studies of applications of neural networks in various fields, ranging from cell-shape classification to micro-trading in finance and to constellation recognition all with their respective source codes.
The book is written for a one-semester graduate or senior-level undergraduate course on artificial neural networks. It is intended to be a reference text for scientists, engineers and researchers in medicine, finance and data mining.
CONTENTS:
Basic principles of ANNs and their early structures are discussed. There are graduate and advanced senior students in artificial intelligence, pattern recognition & image analysis, neural networks, computational economics and finance.
Daniel Graupe, Principles of Artificial Neural Networks (2nd Ed.), Download Principles of Artificial Neural Networks (2nd Ed.), Free Principles of Artificial Neural Networks (2nd Ed.), Principles of Artificial Neural Networks (2nd Ed.) The Principles of Artificial Neural Networks is a second edition. There is a review of principles of artificial neural networks. Group buy.
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