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This book offers a detailed survey of advanced learning algorithms for neural networks and their practical applications. It addresses important topics often underrepresented in other texts, such as weight initialization, mitigation of learning stagnation, and strategies to avoid local minima. The book also tackles challenges in feature selection for large datasets and demonstrates applications across engineering, IT, and bioinformatics domains.
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Publisher: Imperial College Press​
Publishing Year: 2007
ISBN: 978-1-86094-758-2
Pages: 324