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Aggiungi al carrelloPaperback. Condizione: Brand New. 229 pages. 9.25x6.10x0.63 inches. In Stock.
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Editore: Springer, Berlin|Springer Nature Singapore|Springer, 2023
ISBN 10: 9811681953 ISBN 13: 9789811681950
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Neuware -Machine learning (ML) has become a commonplace element in our everyday lives and a standard tool for many fields of science and engineering. To make optimal use of ML, it is essential to understand its underlying principles.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 232 pp. Englisch.
Lingua: Inglese
Editore: Springer Nature Singapore, Springer Nature Singapore, 2023
ISBN 10: 9811681953 ISBN 13: 9789811681950
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Druck auf Anfrage Neuware - Printed after ordering - Machine learning (ML) has become a commonplace element in our everyday lives and astandard tool for many fields of science and engineering. To make optimal use of ML, it isessential to understand its underlying principles.This book approaches ML as the computational implementation of the scientific principle.This principle consists of continuously adapting a model of a given data-generatingphenomenon by minimizing some form of loss incurred by its predictions.The book trains readers to break down various ML applications and methods in terms ofdata, model, and loss, thus helping them to choose from the vast range of ready-made ML methods.The book's three-component approach to ML provides uniform coverage of a wide range ofconcepts and techniques. As a case in point, techniques for regularization, privacy-preservationas well as explainability amount tospecific design choices for the model, data, and loss of a ML method.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Machine learning (ML) has become a commonplace element in our everyday lives and astandard tool for many fields of science and engineering. To make optimal use of ML, it isessential to understand its underlying principles.This book approaches ML as the computational implementation of the scientific principle.This principle consists of continuously adapting a model of a given data-generatingphenomenon by minimizing some form of loss incurred by its predictions.The book trains readers to break down various ML applications and methods in terms ofdata, model, and loss, thus helping them to choose from the vast range of ready-made ML methods.The book's three-component approach to ML provides uniform coverage of a wide range ofconcepts and techniques. As a case in point, techniques for regularization, privacy-preservationas well as explainability amount to specific design choices for the model, data, and loss of a ML method. 232 pp. Englisch.
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Aggiungi al carrelloTaschenbuch. Condizione: Neu. Machine Learning | The Basics | Alexander Jung | Taschenbuch | xvii | Englisch | 2023 | Springer | EAN 9789811681950 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu Print on Demand.