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Añadir al carritohardcover. Condición: Sehr gut. 540 Seiten; 9783031532818.2 Gewicht in Gramm: 2.
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Publicado por Springer Nature Switzerland, Springer Nature Switzerland, 2025
ISBN 10: 3031532848 ISBN 13: 9783031532849
Idioma: Inglés
Librería: AHA-BUCH GmbH, Einbeck, Alemania
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Añadir al carritoTaschenbuch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering.
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Añadir al carritoCondición: As New. Unread book in perfect condition.
Publicado por Springer International Publishing AG, CH, 2024
ISBN 10: 3031532813 ISBN 13: 9783031532818
Idioma: Inglés
Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de America
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Añadir al carritoHardback. Condición: New. 2024 ed.
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Librería: GreatBookPricesUK, Woodford Green, Reino Unido
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Publicado por Springer International Publishing AG, CH, 2024
ISBN 10: 3031532813 ISBN 13: 9783031532818
Idioma: Inglés
Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de America
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Añadir al carritoHardback. Condición: New. 2024 ed.
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Publicado por Springer-Nature New York Inc, 2024
ISBN 10: 3031532813 ISBN 13: 9783031532818
Idioma: Inglés
Librería: Revaluation Books, Exeter, Reino Unido
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Añadir al carritoHardcover. Condición: Brand New. 540 pages. 10.00x7.01x10.00 inches. In Stock.
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Publicado por Springer International Publishing AG, CH, 2024
ISBN 10: 3031532813 ISBN 13: 9783031532818
Idioma: Inglés
Librería: Rarewaves.com UK, London, Reino Unido
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Añadir al carritoHardback. Condición: New. 2024 ed.
Publicado por Springer International Publishing AG, Cham, 2024
ISBN 10: 3031532813 ISBN 13: 9783031532818
Idioma: Inglés
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Añadir al carritoHardcover. Condición: new. Hardcover. This book covers probability and statistics from the machine learning perspective. The chapters of this book belong to three categories:1. The basics of probability and statistics: These chapters focus on the basics of probability and statistics, and cover the key principles of these topics. Chapter 1 provides an overview of the area of probability and statistics as well as its relationship to machine learning. The fundamentals of probability and statistics are covered in Chapters 2 through 5.2. From probability to machine learning: Many machine learning applications are addressed using probabilistic models, whose parameters are then learned in a data-driven manner. Chapters 6 through 9 explore how different models from probability and statistics are applied to machine learning. Perhaps the most important tool that bridges the gap from data to probability is maximum-likelihood estimation, which is a foundational concept from the perspective of machine learning. This concept is explored repeatedly in these chapters.3. Advanced topics: Chapter 10 is devoted to discrete-state Markov processes. It explores the application of probability and statistics to a temporal and sequential setting, although the applications extend to more complex settings such as graphical data. Chapter 11 covers a number of probabilistic inequalities and approximations.The style of writing promotes the learning of probability and statistics simultaneously with a probabilistic perspective on the modeling of machine learning applications. The book contains over 200 worked examples in order to elucidate key concepts. Exercises are included both within the text of the chapters and at the end of the chapters. The book is written for a broad audience, including graduate students, researchers, and practitioners. This book covers probability and statistics from the machine learning perspective. From probability to machine learning: Many machine learning applications are addressed using probabilistic models, whose parameters are then learned in a data-driven manner. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Publicado por Springer Nature Switzerland, Springer International Publishing Mai 2024, 2024
ISBN 10: 3031532813 ISBN 13: 9783031532818
Idioma: Inglés
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 96,29
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Añadir al carritoBuch. Condición: Neu. Neuware -This book covers probability and statistics from the machine learning perspective. The chapters of this book belong to three categories:1. The basics of probability and statistics: These chapters focus on the basics of probability and statistics, and cover the key principles of these topics. Chapter 1 provides an overview of the area of probability and statistics as well as its relationship to machine learning. The fundamentals of probability and statistics are covered in Chapters 2 through 5.2. From probability to machine learning: Many machine learning applications are addressed using probabilistic models, whose parameters are then learned in a data-driven manner. Chapters 6 through 9 explore how different models from probability and statistics are applied to machine learning. Perhaps the most important tool that bridges the gap from data to probability is maximum-likelihood estimation, which is a foundational concept from the perspective of machine learning. This concept is explored repeatedly in these chapters.3. Advanced topics: Chapter 10 is devoted to discrete-state Markov processes. It explores the application of probability and statistics to a temporal and sequential setting, although the applications extend to more complex settings such as graphical data. Chapter 11 covers a number of probabilistic inequalities and approximations.The style of writing promotes the learning of probability and statistics simultaneously with a probabilistic perspective on the modeling of machine learning applications. The book contains over 200 worked examples in order to elucidate key concepts. Exercises are included both within the text of the chapters and at the end of the chapters. The book is written for a broad audience, including graduate students, researchers, and practitioners.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 540 pp. Englisch.
Publicado por Springer International Publishing AG, CH, 2024
ISBN 10: 3031532813 ISBN 13: 9783031532818
Idioma: Inglés
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
EUR 136,64
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Añadir al carritoHardback. Condición: New. 2024 ed.
Librería: Books Puddle, New York, NY, Estados Unidos de America
EUR 129,81
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Añadir al carritoCondición: New. 2024th edition NO-PA16APR2015-KAP.
Publicado por Springer International Publishing AG, Cham, 2024
ISBN 10: 3031532813 ISBN 13: 9783031532818
Idioma: Inglés
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 146,18
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Añadir al carritoHardcover. Condición: new. Hardcover. This book covers probability and statistics from the machine learning perspective. The chapters of this book belong to three categories:1. The basics of probability and statistics: These chapters focus on the basics of probability and statistics, and cover the key principles of these topics. Chapter 1 provides an overview of the area of probability and statistics as well as its relationship to machine learning. The fundamentals of probability and statistics are covered in Chapters 2 through 5.2. From probability to machine learning: Many machine learning applications are addressed using probabilistic models, whose parameters are then learned in a data-driven manner. Chapters 6 through 9 explore how different models from probability and statistics are applied to machine learning. Perhaps the most important tool that bridges the gap from data to probability is maximum-likelihood estimation, which is a foundational concept from the perspective of machine learning. This concept is explored repeatedly in these chapters.3. Advanced topics: Chapter 10 is devoted to discrete-state Markov processes. It explores the application of probability and statistics to a temporal and sequential setting, although the applications extend to more complex settings such as graphical data. Chapter 11 covers a number of probabilistic inequalities and approximations.The style of writing promotes the learning of probability and statistics simultaneously with a probabilistic perspective on the modeling of machine learning applications. The book contains over 200 worked examples in order to elucidate key concepts. Exercises are included both within the text of the chapters and at the end of the chapters. The book is written for a broad audience, including graduate students, researchers, and practitioners. This book covers probability and statistics from the machine learning perspective. From probability to machine learning: Many machine learning applications are addressed using probabilistic models, whose parameters are then learned in a data-driven manner. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Publicado por Springer Nature Switzerland, Springer Nature Switzerland Mai 2025, 2025
ISBN 10: 3031532848 ISBN 13: 9783031532849
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 69,54
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware 540 pp. Englisch.
Librería: Brook Bookstore On Demand, Napoli, NA, Italia
EUR 58,23
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Añadir al carritoCondición: new. Questo è un articolo print on demand.
Publicado por Springer Nature Switzerland, 2024
ISBN 10: 3031532813 ISBN 13: 9783031532818
Idioma: Inglés
Librería: moluna, Greven, Alemania
EUR 81,44
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Añadir al carritoGebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Simple and intuitive discussions of probability and statisticsDiscusses details of applications of mathematical concepts to machine learningProvides mathematical details without losing the reader in complexityCharu C. Aggarwal is a .
Publicado por Springer Nature Switzerland, Springer Nature Switzerland Mai 2025, 2025
ISBN 10: 3031532848 ISBN 13: 9783031532849
Idioma: Inglés
Librería: buchversandmimpf2000, Emtmannsberg, BAYE, Alemania
EUR 69,54
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Añadir al carritoTaschenbuch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book covers probability and statistics from the machine learning perspective. The chapters of this book belong to three categories:Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 540 pp. Englisch.
Publicado por Springer, Berlin, Springer Nature Switzerland, Springer, 2024
ISBN 10: 3031532813 ISBN 13: 9783031532818
Idioma: Inglés
Librería: BuchWeltWeit Ludwig Meier e.K., Bergisch Gladbach, Alemania
EUR 96,29
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Añadir al carritoBuch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book covers probability and statistics from the machine learning perspective. Thechapters of this book belong to three categories:1. The basics of probability and statistics: These chapters focus on the basics of probability and statistics, and cover the key principles of these topics. Chapter 1 provides an overview of the area of probability and statistics as well as its relationship to machine learning. The fundamentals of probability and statistics are covered in Chapters 2 through 5.2. From probability to machine learning: Many machine learning applications are addressed using probabilistic models, whose parameters are then learned in a data-driven manner. Chapters 6 through 9 explore how different models from probability and statistics are applied to machine learning. Perhaps the most important tool that bridges the gap from data to probability is maximum-likelihood estimation, which is a foundational concept from the perspective of machine learning. This concept is explored repeatedly in these chapters.3. Advanced topics: Chapter 10 is devoted to discrete-state Markov processes. It explores the application of probability and statistics to a temporal and sequential setting, although the applications extend to more complex settings such as graphical data. Chapter 11 covers a number of probabilistic inequalities and approximations.The style of writing promotes the learning of probability and statistics simultaneously witha probabilistic perspective on the modeling of machine learning applications. The book contains over 200 worked examples in order to elucidate key concepts. Exercises are included both within the text of the chapters and at the end of the chapters. The book is written for a broad audience, including graduate students, researchers, and practitioners. 522 pp. Englisch.
Librería: Majestic Books, Hounslow, Reino Unido
EUR 117,30
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 120,28
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Librería: Majestic Books, Hounslow, Reino Unido
EUR 134,47
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Librería: Biblios, Frankfurt am main, HESSE, Alemania
EUR 139,99
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