Flach Machine Learning Hardback

ISBN 13: 9781107096394

Machine Learning Hardback

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9781107096394: Machine Learning Hardback
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Machine Learning brings together all the state-of-the-art methods for making sense of data. With hundreds of worked examples and explanatory figures, the book explains the principles behind these methods in an intuitive yet precise manner and will appeal to novice and experienced readers alike.

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"This textbook is clearly written and well organized. Starting from the basics, the author skillfully guides the reader through his learning process by providing useful facts and insight into the behavior of several machine learning techniques, as well as the high-level pseudocode of many key algorithms." < /br>Fernando Berzal, Computing Reviews

Biografía del autor:

Peter Flach has more than twenty years of experience in machine learning teaching and research. He is Editor-in-Chief of Machine Learning and Program Co-Chair of the 2009 ACM Conference on Knowledge Discovery and Data Mining and the 2012 European Conference on Machine Learning and Data Mining. His research spans all aspects of machine learning, from knowledge representation and the use of logic to learn from highly structured data to the analysis and evaluation of machine learning models and methods to large-scale data mining. He is particularly known for his innovative use of Receiver Operating Characteristic (ROC) analysis for understanding and improving machine learning methods. These innovations have proved their effectiveness in a number of invited talks and tutorials and now form the backbone of this book.

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Peter Flach
ISBN 10: 1107096391 ISBN 13: 9781107096394
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Descripción Condición: Brand New. Brand New Paperback International Edition, Perfect Condition. Printed in English. Excellent Quality, Service and customer satisfaction guaranteed!. Nº de ref. del artículo: AIND-63642

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Descripción Condición: New. Brand New Paperback International Edition.We Ship to PO BOX Address also. EXPEDITED shipping option also available for faster delivery.This item may ship fro the US or other locations in India depending on your location and availability. Nº de ref. del artículo: AUSBNEW-63642

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Publicado por Cambridge University Press (2012)
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Descripción Cambridge University Press, 2012. HRD. Condición: New. New Book. Shipped from UK in 4 to 14 days. Established seller since 2000. Nº de ref. del artículo: FM-9781107096394

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Descripción CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2012. Hardback. Condición: New. New. Language: English . Brand New Book. As one of the most comprehensive machine learning texts around, this book does justice to the field s incredible richness, but without losing sight of the unifying principles. Peter Flach s clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. He covers a wide range of logical, geometric and statistical models and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook. Nº de ref. del artículo: AAA9781107096394

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Descripción CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2012. Hardback. Condición: New. New. Language: English . Brand New Book. As one of the most comprehensive machine learning texts around, this book does justice to the field s incredible richness, but without losing sight of the unifying principles. Peter Flach s clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. He covers a wide range of logical, geometric and statistical models and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook. Nº de ref. del artículo: AAA9781107096394

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Descripción Cambridge University Press. Hardback. Condición: New. New copy - Usually dispatched within 2 working days. Nº de ref. del artículo: B9781107096394

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Descripción Cambridge University Press, 2012. Hardcover. Condición: New. Nº de ref. del artículo: DADAX1107096391

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Descripción Cambridge University Press, 2012. Hardcover. Condición: Brand New. 1st edition. 410 pages. 9.69x0.94x7.48 inches. In Stock. Nº de ref. del artículo: __1107096391

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Descripción 2012. Hardback. Condición: NEW. 9781107096394 This listing is a new book, a title currently in-print which we order directly and immediately from the publisher. For all enquiries, please contact Herb Tandree Philosophy Books directly - customer service is our primary goal. Nº de ref. del artículo: HTANDREE0486674

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Descripción CAMBRIDGE UNIVERSITY PRESS, United Kingdom, 2012. Hardback. Condición: New. New. Language: English . This book usually ship within 10-15 business days and we will endeavor to dispatch orders quicker than this where possible. Brand New Book. As one of the most comprehensive machine learning texts around, this book does justice to the field s incredible richness, but without losing sight of the unifying principles. Peter Flach s clear, example-based approach begins by discussing how a spam filter works, which gives an immediate introduction to machine learning in action, with a minimum of technical fuss. Flach provides case studies of increasing complexity and variety with well-chosen examples and illustrations throughout. He covers a wide range of logical, geometric and statistical models and state-of-the-art topics such as matrix factorisation and ROC analysis. Particular attention is paid to the central role played by features. The use of established terminology is balanced with the introduction of new and useful concepts, and summaries of relevant background material are provided with pointers for revision if necessary. These features ensure Machine Learning will set a new standard as an introductory textbook. Nº de ref. del artículo: BTE9781107096394

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