Pattern Recognition and Machine Learning for Self-study I: Supervised Learning - Couverture rigide

Ishii, Kenichiro ; Ueda, Naonori ; Maeda, Eisaku ; Murase, Hiroshi

9789819514779: Pattern Recognition and Machine Learning for Self-study I: Supervised Learning

Couverture rigide

ISBN 10 : 9819514770 ISBN 13 : 9789819514779

Editeur : Springer Verlag, Singapore, 2026

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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.

Unsupervised learning will be discussed in a sequel.

Les informations fournies dans la section � Synopsis � peuvent faire r�f�rence � une autre �dition de ce titre.

�diteur: Springer Verlag, Singapore
Date d'�dition: 2026
Langue: anglais
ISBN 10: 9819514770
ISBN 13: 9789819514779
Reliure: Reli�
Nombre de pages: 479
Coordonn�es du fabricant: Springer Nature Customer Service Center GmbH
ProductSafety@springernature.com

Europaplatz 3,69115 Heidelberg, Germany
Heidelberg
69115
Allemagne

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Pattern Recognition and Machine Learning for Self-Study I (Hardcover)

Kenichiro Ishii

Edit� par Springer Verlag, Singapore, Singapore, 2026

ISBN 10 : 9819514770 ISBN 13 : 9789819514779

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Hardcover. Etat : new. Hardcover. 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. Unsupervised learning will be discussed in a sequel. 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N� de r�f. du vendeur 9789819514779

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Pattern Recognition and Machine Learning for Self-Study I: Supervised Learning

Ishii, Kenichiro (Author)/ Ueda, Naonori (Author)/ Maeda, Eisaku (Author)/ Murase, Hiroshi (Author)

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ISBN 10 : 9819514770 ISBN 13 : 9789819514779

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Pattern Recognition and Machine Learning for Self-Study I

Naonori Ueda

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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 r�f. du vendeur 9789819514779

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Pattern Recognition and Machine Learning for Self-Study I

Ishii, Kenichiro; Ueda, Naonori; Maeda, Eisaku; Murase, Hiroshi

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ISBN 10 : 9819514770 ISBN 13 : 9789819514779

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Pattern Recognition and Machine Learning for Self-Study I (Hardcover)

Kenichiro Ishii

Edit� par Springer Verlag, Singapore, Singapore, 2026

ISBN 10 : 9819514770 ISBN 13 : 9789819514779

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Hardcover. Etat : new. Hardcover. 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. Unsupervised learning will be discussed in a sequel. 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N� de r�f. du vendeur 9789819514779

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Pattern Recognition and Machine Learning for Self-Study I: Supervised Learning (Springer Asia Pacific Mathematics Series, 1)

Ishii, Kenichiro; Ueda, Naonori; Maeda, Eisaku; Murase, Hiroshi

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ISBN 10 : 9819514770 ISBN 13 : 9789819514779

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Pattern Recognition and Machine Learning for Self-Study I: Supervised Learning (Springer Asia Pacific Mathematics Series, 1)

Ishii, Kenichiro; Ueda, Naonori; Maeda, Eisaku; Murase, Hiroshi

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ISBN 10 : 9819514770 ISBN 13 : 9789819514779

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Pattern Recognition and Machine Learning for Self-Study I: Supervised Learning (Springer Asia Pacific Mathematics Series, 1)

Ishii, Kenichiro; Ueda, Naonori; Maeda, Eisaku; Murase, Hiroshi

Edit� par Springer, 2026

ISBN 10 : 9819514770 ISBN 13 : 9789819514779

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Pattern Recognition and Machine Learning for Self-Study I

Hiroshi Murase

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Buch. Etat : Neu. This item is printed on demand - Print on Demand Titel. 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. Unsupervised learning will be discussed in a sequel.Springer Nature Customer Service Center GmbH, Europaplatz 3,69115 Heidelberg, Germany, Heidelberg 480 pp. Englisch. N� de r�f. du vendeur 9789819514779

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