Waic Wbic Python Stan by Suzuki Joe (19 results)

paperback. Condition: Very Good.

Paperback. Condition: new. Paperback. Master the art of machine learning and data science by diving into the essence of mathematical logic with this comprehensive textbook. This book focuses on the widely applicable information criterion (WAIC), also described as the Watanabe-Akaike information criterion, and the widely applicable Bayesian information criterion (WBIC), also described as the Watanabe Bayesian information criterion. The book expertly guides you through relevant mathematical problems while also providing hands-on experience with programming in Python and Stan. Whether youre a data scientist looking to refine your model selection process or a researcher who wants to explore the latest developments in Bayesian statistics, this accessible guide will give you a firm grasp of Watanabe Bayesian Theory.The key features of this indispensable book include:A clear and self-contained writing style, ensuring ease of understanding for readers at various levels of expertise.100 carefully selected exercises accompanied by solutions in the main text, enabling readers to effectively gauge their progress and comprehension.A comprehensive guide to Sumio Watanabes groundbreaking Bayes theory, demystifying a subject once considered too challenging even for seasoned statisticians.Detailed source programs and Stan codes that will enhance readers grasp of the mathematical concepts presented.A streamlined approach to algebraic geometry topics in Chapter 6, making Bayes theory more accessible and less daunting.Embark on your machine learning and data science journey with this essential textbook and unlock the full potential of WAIC and WBIC today! Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Condition: New.

Condition: New.

Condition: New.

Condition: New.

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: New. In English.

Paperback. Condition: Brand New. 254 pages. 9.25x6.10x0.54 inches. In Stock.

Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - Master the art of machine learning and data science by diving into the essence of mathematical logic with this comprehensive textbook.This book focuses on the widely applicable information criterion (WAIC), also described as the Watanabe-Akaike information criterion, and the widely applicable Bayesian information criterion (WBIC), also described as the Watanabe Bayesian information criterion. The book expertly guides you through relevant mathematical problems while also providing hands-on experience with programming in Python and Stan. Whether you're a data scientist looking to refine your model selection process or a researcher who wants to explore the latest developments in Bayesian statistics, this accessible guide will give you a firm grasp of Watanabe Bayesian Theory.The key features of this indispensable book include:A clear and self-contained writing style, ensuring ease of understanding for readers at various levels of expertise.100 carefully selected exercises accompanied by solutions in the main text, enabling readers to effectively gauge their progress and comprehension.A comprehensive guide to Sumio Watanabe's groundbreaking Bayes theory, demystifying a subject once considered too challenging even for seasoned statisticians.Detailed source programs and Stan codes that will enhance readers' grasp of the mathematical concepts presented.A streamlined approach to algebraic geometry topics in Chapter 6, making Bayes theory more accessible and less daunting.Embark on your machine learning and data science journey with this essential textbook and unlock the full potential of WAIC and WBIC today.…

Paperback. Condition: new. Paperback. Master the art of machine learning and data science by diving into the essence of mathematical logic with this comprehensive textbook. This book focuses on the widely applicable information criterion (WAIC), also described as the Watanabe-Akaike information criterion, and the widely applicable Bayesian information criterion (WBIC), also described as the Watanabe Bayesian information criterion. The book expertly guides you through relevant mathematical problems while also providing hands-on experience with programming in Python and Stan. Whether youre a data scientist looking to refine your model selection process or a researcher who wants to explore the latest developments in Bayesian statistics, this accessible guide will give you a firm grasp of Watanabe Bayesian Theory.The key features of this indispensable book include:A clear and self-contained writing style, ensuring ease of understanding for readers at various levels of expertise.100 carefully selected exercises accompanied by solutions in the main text, enabling readers to effectively gauge their progress and comprehension.A comprehensive guide to Sumio Watanabes groundbreaking Bayes theory, demystifying a subject once considered too challenging even for seasoned statisticians.Detailed source programs and Stan codes that will enhance readers grasp of the mathematical concepts presented.A streamlined approach to algebraic geometry topics in Chapter 6, making Bayes theory more accessible and less daunting.Embark on your machine learning and data science journey with this essential textbook and unlock the full potential of WAIC and WBIC today! Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…

Taschenbuch. Condition: Neu. WAIC and WBIC with Python Stan | 100 Exercises for Building Logic | Joe Suzuki | Taschenbuch | xii | Englisch | 2023 | Springer | EAN 9789819938407 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

Condition: Sehr gut. Zustand: Sehr gut | Sprache: Englisch | Produktart: Bücher | Master the art of machine learning and data science by diving into the essence of mathematical logic with this comprehensive textbook. This book focuses on the widely applicable information criterion (WAIC), also described as the Watanabe-Akaike information criterion, and the widely applicable Bayesian information criterion (WBIC), also described as the Watanabe Bayesian information criterion. The book expertly guides you through relevant mathematical problems while also providing hands-on experience with programming in Python and Stan. Whether yoüre a data scientist looking to refine your model selection process or a researcher who wants to explore the latest developments in Bayesian statistics, this accessible guide will give you a firm grasp of Watanabe Bayesian Theory.The key features of this indispensable book include:A clear and self-contained writing style, ensuring ease of understanding for readers at various levels of expertise.100 carefully selected exercises accompanied by solutions in the main text, enabling readers to effectively gauge their progress and comprehension.A comprehensive guide to Sumio Watanabe¿s groundbreaking Bayes theory, demystifying a subject once considered too challenging even for seasoned statisticians.Detailed source programs and Stan codes that will enhance readers¿ grasp of the mathematical concepts presented.A streamlined approach to algebraic geometry topics in Chapter 6, making Bayes theory more accessible and less daunting.Embark on your machine learning and data science journey with this essential textbook and unlock the full potential of WAIC and WBIC today.…

Condition: new. Questo è un articolo print on demand.

Paperback. Condition: Brand New. 254 pages. 9.25x6.10x0.54 inches. In Stock. This item is printed on demand.

Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -Master the art of machine learning and data science by diving into the essence of mathematical logic with this comprehensive textbook.This book focuses on the widely applicable information criterion (WAIC), also described as the Watanabe-Akaike information criterion, and the widely applicable Bayesian information criterion (WBIC), also described as the Watanabe Bayesian information criterion. The book expertly guides you through relevant mathematical problems while also providing hands-on experience with programming in Python and Stan. Whether you're a data scientist looking to refine your model selection process or a researcher who wants to explore the latest developments in Bayesian statistics, this accessible guide will give you a firm grasp of Watanabe Bayesian Theory.The key features of this indispensable book include:A clear and self-contained writing style, ensuring ease of understanding for readers at various levels of expertise.100 carefully selected exercises accompanied by solutions in the main text, enabling readers to effectively gauge their progress and comprehension.A comprehensive guide to Sumio Watanabe's groundbreaking Bayes theory, demystifying a subject once considered too challenging even for seasoned statisticians.Detailed source programs and Stan codes that will enhance readers' grasp of the mathematical concepts presented.A streamlined approach to algebraic geometry topics in Chapter 6, making Bayes theory more accessible and less daunting.Embark on your machine learning and data science journey with this essential textbook and unlock the full potential of WAIC and WBIC today! 256 pp. Englisch.…

Kartoniert / Broschiert. Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Focuses on widely applicable information criterion (WAIC) & widely applicable Bayesian information criterion (WBIC)Presents 100 carefully selected exercises accompanied by solutions in the main textContains detailed source programs and Stan.…

Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -Master the art of machine learning and data science by diving into the essence of mathematical logic with this comprehensive textbook. This book focuses on the widely applicable information criterion (WAIC), also described as the Watanabe-Akaike information criterion, and the widely applicable Bayesian information criterion (WBIC), also described as the Watanabe Bayesian information criterion. The book expertly guides you through relevant mathematical problems while also providing hands-on experience with programming in Python and Stan. Whether you're a data scientist looking to refine your model selection process or a researcher who wants to explore the latest developments in Bayesian statistics, this accessible guide will give you a firm grasp of Watanabe Bayesian Theory.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 256 pp. Englisch.…