Machine learning basics de jung alexander (25 resultados)

Condición: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.

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Condición: New. 1st ed. 2022 edition NO-PA16APR2015-KAP.

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Paperback. Condición: Brand New. 229 pages. 9.25x6.10x0.63 inches. In Stock.

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Taschenbuch. Condición: 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.…

Buch. Condición: 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.…

Taschenbuch. Condición: Neu. Machine Learning | The Basics | Alexander Jung | Taschenbuch | Machine Learning: Foundations, Methodologies, and Applications | 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.…

Condición: Hervorragend. Zustand: Hervorragend | Sprache: Englisch | Produktart: Bücher | 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. This book approaches ML as the computational implementation of the scientific principle. This principle consists of continuously adapting a model of a given data-generating phenomenon by minimizing some form of loss incurred by its predictions. The book trains readers to break down various ML applications and methods in terms of data, 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 of concepts and techniques. As a case in point, techniques for regularization, privacy-preservation as well as explainability amount tospecific design choices for the model, data, and loss of a ML method.…

Condición: Buone. inglese Condizioni dell'esterno: Discrete con difetti, segni d'uso Condizioni dell'interno: Buone.

Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. The book trains readers to break down various ML applications and methods in terms of data, 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.…