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Añadir al carritoTaschenbuch. Condición: Neu. Supervised Machine Learning: A Comprehensive Guide | Subir Gupta | Taschenbuch | Englisch | 2024 | LAP LAMBERT Academic Publishing | EAN 9786207844548 | Verantwortliche Person für die EU: SIA OmniScriptum Publishing, Brivibas Gatve 197, 1039 RIGA, LETTLAND, customerservice[at]vdm-vsg[dot]de | Anbieter: preigu.
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 56 pp. Englisch.
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -The book 'Supervised Machine Learning: A Comprehensive Guide' by Dr. Subir Gupta aims to provide an in-depth understanding of supervised machine learning algorithms. It targets students, professionals, and researchers, offering clear explanations and practical applications. The book is divided into three main sections: an introduction to the fundamental concepts and types of supervised learning, a detailed exploration of regression algorithms, and an extensive examination of classification algorithms. Each algorithm is explained with definitions, practical uses, pseudocode, and discussions of their limitations. The guide is designed to be a valuable resource for anyone looking to apply machine learning techniques effectively to solve real-world problems.VDM Verlag, Dudweiler Landstraße 99, 66123 Saarbrücken 56 pp. Englisch.
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ISBN 10: 6207844548 ISBN 13: 9786207844548
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The book 'Supervised Machine Learning: A Comprehensive Guide' by Dr. Subir Gupta aims to provide an in-depth understanding of supervised machine learning algorithms. It targets students, professionals, and researchers, offering clear explanations and practical applications. The book is divided into three main sections: an introduction to the fundamental concepts and types of supervised learning, a detailed exploration of regression algorithms, and an extensive examination of classification algorithms. Each algorithm is explained with definitions, practical uses, pseudocode, and discussions of their limitations. The guide is designed to be a valuable resource for anyone looking to apply machine learning techniques effectively to solve real-world problems.