Isbn: 9783031609497 - fundamentals of pattern recognition and machine learning (18 resultados)

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Condición: New. Second Edition 2024 NO-PA16APR2015-KAP.

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Hardcover. Condición: Brand New. 2nd edition. 400 pages. 9.25x6.10x10.00 inches. In Stock.

Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book is a concise but thorough introduction tothe tools commonly used in pattern recognition and machine learning, including classification, dimensionality reduction, regression, and clustering, as well as recent popular topics such as deep neural networks and Gaussian process regression. The Second Edition is thoroughly revised, featuring a new chapter on the emerging topic of physics-informed machine learning and additional material on deep neural networks.Combining theory and practice, this book is suitable for the graduate or advanced undergraduate levelclassroom and self-study. It fills the need of a mathematically-rigorous text that is relevant to the practitioner as well, with datasets from applications in bioinformatics and materials informatics used throughout to illustrate the theory. These datasets are available from the book website to be used in end-of-chapter coding assignments based on python and Keras/Tensorflow. All plots in the text were generated using python scripts and jupyter not Elektronisches Buch, which can be downloaded from the book website.…

Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book is a concise but thorough introduction tothe tools commonly used in pattern recognition and machine learning, including classification, dimensionality reduction, regression, and clustering, as well as recent popular topics such as deep neural networks and Gaussian process regression. The Second Edition is thoroughly revised, featuring a new chapter on the emerging topic of physics-informed machine learning and additional material on deep neural networks.Combining theory and practice, this book is suitable for the graduate or advanced undergraduate levelclassroom and self-study. It fills the need of a mathematically-rigorous text that is relevant to the practitioner as well, with datasets from applications in bioinformatics and materials informatics used throughout to illustrate the theory. These datasets are available from the book website to be used in end-of-chapter coding assignments based on python and Keras/Tensorflow. All plots in the text were generated using python scripts and jupyter not Elektronisches Buch, which can be downloaded from the book website. 400 pp. Englisch.…

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Buch. Condición: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book is a concise but thorough introduction to the tools commonly used in pattern recognition and machine learning, including classification, dimensionality reduction, regression, and clustering, as well as recent popular topics such as deep neural networks and Gaussian process regression. The Second Edition is thoroughly revised, featuring a new chapter on the emerging topic of physics-informed machine learning and additional material on deep neural networks.Combining theory and practice, this book is suitable for the graduate or advanced undergraduate level classroom and self-study. It fills the need of a mathematically-rigorous text that is relevant to the practitioner as well, with datasets from applications in bioinformatics and materials informatics used throughout to illustrate the theory. These datasets are available from the book website to be used in end-of-chapter coding assignments based on python and Keras/Tensorflow. All plots in the text were generated using python scripts and jupyter not Elektronisches Buch, which can be downloaded from the book website.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 424 pp. Englisch.…