Items related to Handbook of Evolutionary Machine Learning (Genetic...
- PublisherSpringer
- Publication date2023
- ISBN 10 9819938139
- ISBN 13 9789819938131
- BindingHardcover
- LanguageEnglish
- Edition number1
- Number of pages784
- EditorBanzhaf Wolfgang, Machado Penousal, Zhang Mengjie
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Handbook of Evolutionary Machine Learning
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HANDBOOK OF EVOLUTIONARY MACHINE LEARNING
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Handbook Of Evolutionary Machine Learning
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Handbook of Evolutionary Machine Learning
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Handbook of Evolutionary Machine Learning
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Handbook of Evolutionary Machine Learning
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Handbook of Evolutionary Machine Learning (Genetic and Evolutionary Computation)
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Handbook of Evolutionary Machine Learning
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Springer, Berlin|Springer Nature Singapore|Springer, 2023
ISBN 10: 9819938139
ISBN 13: 9789819938131
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Hardcover
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Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. This book, written by leading international researchers of evolutionary approaches to machine learning, explores various ways evolution can address machine learning problems and improve current methods of machine learning. Topics in this book are organized . Seller Inventory # 873623245
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Handbook of Evolutionary Machine Learning (Genetic and Evolutionary Computation)
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Handbook of Evolutionary Machine Learning
Published by
Springer Nature Singapore, Springer Nature Singapore Nov 2023, 2023
ISBN 10: 9819938139
ISBN 13: 9789819938131
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Hardcover
Seller: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Germany
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Buch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book, written by leading international researchers of evolutionary approaches to machine learning, explores various ways evolution can address machine learning problems and improve current methods of machine learning. Topics in this book are organized into five parts. The first part introduces some fundamental concepts and overviews of evolutionary approaches to the three different classes of learning employed in machine learning. The second addresses the use of evolutionary computation as a machine learning technique describing methodologic improvements for evolutionary clustering, classification, regression, and ensemble learning. The third part explores the connection between evolution and neural networks, in particular the connection to deep learning, generative and adversarial models as well as the exciting potential of evolution with large language models. The fourth part focuses on the use of evolutionary computation for supporting machine learning methods. This includes methodological developments for evolutionary data preparation, model parametrization, design, and validation. The final part covers several chapters on applications in medicine, robotics, science, finance, and other disciplines. Readers find reviews of application areas and can discover large-scale, real-world applications of evolutionary machine learning to a variety of problem domains.This book will serve as an essential reference for researchers, postgraduate students, practitioners in industry and all those interested in evolutionary approaches to machine learning. 784 pp. Englisch. Seller Inventory # 9789819938131
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