Synopsis
mso-fareast-language: EN-US;">The following points make this book suitable for self-study by beginners.
(1) The book is self-contained, so that the reader does not need to refer to other books or literature.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
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Pattern Recognition and Machine Learning for Self-Study I
Edité par
Springer Verlag, Singapore Jun 2026, 2026
ISBN 10 : 9819514770
ISBN 13 : 9789819514779
Neuf
Couverture rigide
Vendeur : BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book explains the basic principles of pattern recognition (PR) and machine learning (ML) in an easy-to-understand manner for beginners who are trying to learn these principles on their own. Readers with a basic knowledge of linear algebra and probability theory will find it easy to follow.Many excellent books in this field have been published in the past. However, these books are not necessarily intended for self-study by beginners.This book limits the topics to the minimum essential themes that beginners should learn, and explains them in detail. This book focuses on supervised learning, first introducing classical but important methods that have contributed to the development of the field. It then explains various methods that have since attracted attention. In explaining these methods, the book also provides a historical account of how new technologies were created as a result of combining classical ideas. The book emphasizes that Bayes decision rule is a fundamental concept in PR and ML.The following points make this book suitable for self-study by beginners.(1) The book is self-contained, so that the reader does not need to refer to other books or literature. (2) To deepen the reader's understanding, exercises are provided at the end of each chapter with detailed solutions available online.(3) To promote the reader's intuitive understanding, the book presents as many concrete examples as possible.(4) Coffee Break columns introduce knowledge and know-how from the author's experience. 461 pp. Englisch. N° de réf. du vendeur 9789819514779
Acheter neuf
EUR 74,89
Expédition à EUR 23
Expédition depuis Allemagne vers Etats-Unis
Expédition depuis Allemagne vers Etats-Unis
Quantité disponible : 2 disponible(s)
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Pattern Recognition and Machine Learning for Self-Study I: Supervised Learning (Springer Asia Pacific Mathematics Series, 1)
Vendeur : Majestic Books, Hounslow, Royaume-Uni
Évaluation du vendeur 4 sur 5 étoiles
Etat : New. N° de réf. du vendeur 409544620
Acheter neuf
EUR 123,41
Expédition à EUR 7,53
Expédition depuis Royaume-Uni vers Etats-Unis
Expédition depuis Royaume-Uni vers Etats-Unis
Quantité disponible : 4 disponible(s)
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Pattern Recognition and Machine Learning for Self-Study I : Supervised Learning
Edité par
Springer Nature Singapore, 2026
ISBN 10 : 9819514770
ISBN 13 : 9789819514779
Neuf
Couverture rigide
Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne
Évaluation du vendeur 5 sur 5 étoiles
Buch. Etat : Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explains the basic principles of pattern recognition (PR) and machine learning (ML) in an easy-to-understand manner for beginners who are trying to learn these principles on their own. Readers with a basic knowledge of linear algebra and probability theory will find it easy to follow.Many excellent books in this field have been published in the past. However, these books are not necessarily intended for self-study by beginners.This book limits the topics to the minimum essential themes that beginners should learn, and explains them in detail. This book focuses on supervised learning, first introducing classical but important methods that have contributed to the development of the field. It then explains various methods that have since attracted attention. In explaining these methods, the book also provides a historical account of how new technologies were created as a result of combining classical ideas. The book emphasizes that Bayes decision rule is a fundamental concept in PR and ML.The following points make this book suitable for self-study by beginners.(1) The book is self-contained, so that the reader does not need to refer to other books or literature. (2) To deepen the reader's understanding, exercises are provided at the end of each chapter with detailed solutions available online.(3) To promote the reader's intuitive understanding, the book presents as many concrete examples as possible.(4) Coffee Break columns introduce knowledge and know-how from the author's experience. N° de réf. du vendeur 9789819514779
Acheter neuf
EUR 81,73
Expédition à EUR 64,40
Expédition depuis Allemagne vers Etats-Unis
Expédition depuis Allemagne vers Etats-Unis
Quantité disponible : 2 disponible(s)