Gebunden. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Provides representative tools used for machine learning and metaheuristic algorithms&nbspFocuses on the theory and application of metaheuristic algorithms in machine learning, including hybridization and implementations . Seller Inventory # 458553028

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Metaheuristics in Machine Learning: Theory and Applications

Diego Oliva

Published by Springer International Publishing Jul 2021, 2021

ISBN 10: 3030705412 ISBN 13: 9783030705411

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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 is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms.The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities. 788 pp. Englisch. Seller Inventory # 9783030705411

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Metaheuristics in Machine Learning: Theory and Applications

Diego Oliva

Published by Springer International Publishing, 2021

ISBN 10: 3030705412 ISBN 13: 9783030705411

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Seller: AHA-BUCH GmbH, Einbeck, Germany

Seller rating 5 out of 5 stars

Buch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is a collection of the most recent approaches that combine metaheuristics and machine learning. Some of the methods considered in this book are evolutionary, swarm, machine learning, and deep learning. The chapters were classified based on the content; then, the sections are thematic. Different applications and implementations are included; in this sense, the book provides theory and practical content with novel machine learning and metaheuristic algorithms.The chapters were compiled using a scientific perspective. Accordingly, the book is primarily intended for undergraduate and postgraduate students of Science, Engineering, and Computational Mathematics and is useful in courses on Artificial Intelligence, Advanced Machine Learning, among others. Likewise, the book is useful for research from the evolutionary computation, artificial intelligence, and image processing communities. Seller Inventory # 9783030705411

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