mansour eddaly (23 resultados)

Paperback. Condición: Brand New. 240 pages. 9.21x6.14x0.51 inches. In Stock.

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Condición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | Using metaheuristics to enhance machine learning techniques has become trendy and has achieved major successes in both supervised (classification and regression) and unsupervised (clustering and rule mining) problems. Furthermore, automatically generating programs via metaheuristics, as a form of evolutionary computation and swarm intelligence, has now gained widespread popularity. This book investigates different ways of integrating metaheuristics into machine learning techniques, from both theoretical and practical standpoints. It explores how metaheuristics can be adapted in order to enhance machine learning tools and presents an overview of the main metaheuristic programming methods. Moreover, real-world applications are provided for illustration, e.g., in clustering, big data, machine health monitoring, underwater sonar targets, and banking.

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Taschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Using metaheuristics to enhance machine learning techniques has become trendy and has achieved major successes in both supervised (classification and regression) and unsupervised (clustering and rule mining) problems. Furthermore, automatically generating programs via metaheuristics, as a form of evolutionary computation and swarm intelligence, has now gained widespread popularity. This book investigates different ways of integrating metaheuristics into machine learning techniques, from both theoretical and practical standpoints. It explores how metaheuristics can be adapted in order to enhance machine learning tools and presents an overview of the main metaheuristic programming methods. Moreover, real-world applications are provided for illustration, e.g., in clustering, big data, machine health monitoring, underwater sonar targets, and banking.

Taschenbuch. Condición: Neu. Neuware -Using metaheuristics to enhance machine learning techniques has become trendy and has achieved major successes in both supervised (classification and regression) and unsupervised (clustering and rule mining) problems. Furthermore, automatically generating programs via metaheuristics, as a form of evolutionary computation and swarm intelligence, has now gained widespread popularity. This book investigates different ways of integrating metaheuristics into machine learning techniques, from both theoretical and practical standpoints. It explores how metaheuristics can be adapted in order to enhance machine learning tools and presents an overview of the main metaheuristic programming methods. Moreover, real-world applications are provided for illustration, e.g., in clustering, big data, machine health monitoring, underwater sonar targets, and banking.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 240 pp. Englisch.

Buch. Condición: Neu. Neuware -Using metaheuristics to enhance machine learning techniques has become trendy and has achieved major successes in both supervised (classification and regression) and unsupervised (clustering and rule mining) problems. Furthermore, automatically generating programs via metaheuristics, as a form of evolutionary computation and swarm intelligence, has now gained widespread popularity. This book investigates different ways of integrating metaheuristics into machine learning techniques, from both theoretical and practical standpoints. It explores how metaheuristics can be adapted in order to enhance machine learning tools and presents an overview of the main metaheuristic programming methods. Moreover, real-world applications are provided for illustration, e.g., in clustering, big data, machine health monitoring, underwater sonar targets, and banking.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 240 pp. Englisch.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - Using metaheuristics to enhance machine learning techniques has become trendy and has achieved major successes in both supervised (classification and regression) and unsupervised (clustering and rule mining) problems. Furthermore, automatically generating programs via metaheuristics, as a form of evolutionary computation and swarm intelligence, has now gained widespread popularity. This book investigates different ways of integrating metaheuristics into machine learning techniques, from both theoretical and practical standpoints. It explores how metaheuristics can be adapted in order to enhance machine learning tools and presents an overview of the main metaheuristic programming methods. Moreover, real-world applications are provided for illustration, e.g., in clustering, big data, machine health monitoring, underwater sonar targets, and banking.

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Condición: new. Questo è un articolo print on demand.

Condición: new. Questo è un articolo print on demand.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Presents latest developments in integrating metaheuristics into machine learning techniquesIllustrates practical applications of metaheuristics in machine learningOffers an overview of main metaheuristic programming methodsMan.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Using metaheuristics to enhance machine learning techniques has become trendy and has achieved major successes in both supervised (classification and regression) and unsupervised (clustering and rule mining) problems. Furthermore, automatically generating p.

Taschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Using metaheuristics to enhance machine learning techniques has become trendy and has achieved major successes in both supervised (classification and regression) and unsupervised (clustering and rule mining) problems. Furthermore, automatically generating programs via metaheuristics, as a form of evolutionary computation and swarm intelligence, has now gained widespread popularity. This book investigates different ways of integrating metaheuristics into machine learning techniques, from both theoretical and practical standpoints. It explores how metaheuristics can be adapted in order to enhance machine learning tools and presents an overview of the main metaheuristic programming methods. Moreover, real-world applications are provided for illustration, e.g., in clustering, big data, machine health monitoring, underwater sonar targets, and banking. 240 pp. Englisch.

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Using metaheuristics to enhance machine learning techniques has become trendy and has achieved major successes in both supervised (classification and regression) and unsupervised (clustering and rule mining) problems. Furthermore, automatically generating programs via metaheuristics, as a form of evolutionary computation and swarm intelligence, has now gained widespread popularity. This book investigates different ways of integrating metaheuristics into machine learning techniques, from both theoretical and practical standpoints. It explores how metaheuristics can be adapted in order to enhance machine learning tools and presents an overview of the main metaheuristic programming methods. Moreover, real-world applications are provided for illustration, e.g., in clustering, big data, machine health monitoring, underwater sonar targets, and banking. 240 pp. Englisch.

Taschenbuch. Condición: Neu. Metaheuristics for Machine Learning | New Advances and Tools | Mansour Eddaly (u. a.) | Taschenbuch | xv | Englisch | 2024 | Springer | EAN 9789811938900 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.

Buch. Condición: Neu. Metaheuristics for Machine Learning | New Advances and Tools | Mansour Eddaly (u. a.) | Buch | xv | Englisch | 2023 | Springer | EAN 9789811938870 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.