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Sinopsis
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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Acerca 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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Machine Learning
Publicado por
Cambridge University Press, 2012
ISBN 10: 1107096391
ISBN 13: 9781107096394
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Machine Learning: The Art and Science of Algorithms that Make Sense of Data
Publicado por
Cambridge University Press, 2012
ISBN 10: 1107096391
ISBN 13: 9781107096394
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Machine Learning: The Art and Science of Algorithms that Make Sense of Data
Publicado por
Cambridge University Press, 2012
ISBN 10: 1107096391
ISBN 13: 9781107096394
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Machine Learning: The Art and Science of Algorithms that Make Sense of Data
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Cambridge University Press, 2012
ISBN 10: 1107096391
ISBN 13: 9781107096394
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Hardcover. Condición: Brand New. 1st edition. 410 pages. 9.69x0.94x7.48 inches. In Stock. This item is printed on demand. Nº de ref. del artículo: __1107096391
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Machine Learning: The Art and Science of Algorithms that Make Sense of Data
Publicado por
Cambridge University Press, 2012
ISBN 10: 1107096391
ISBN 13: 9781107096394
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Condición: good. Supports Goodwill of Silicon Valley job training programs. The cover and pages are in Good condition! Any other included accessories are also in Good condition showing use. Use can include some highlighting and writing, page and cover creases as well as other types visible wear. Nº de ref. del artículo: GWSVV.1107096391.G
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Machine Learning: The Art and Science of Algorithms that Make Sense of Data
Publicado por
Cambridge University Press, 2012
ISBN 10: 1107096391
ISBN 13: 9781107096394
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Machine Learning (Hardcover)
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Cambridge University Press, Cambridge, 2012
ISBN 10: 1107096391
ISBN 13: 9781107096394
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Librería: CitiRetail, Stevenage, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Hardcover. Condición: new. Hardcover. 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. 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. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. Nº de ref. del artículo: 9781107096394
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Machine Learning: The Art and Science of Algorithms that Make Sense of Data
Publicado por
Cambridge University Press, 2012
ISBN 10: 1107096391
ISBN 13: 9781107096394
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Machine Learning
Publicado por
Cambridge University Press, 2018
ISBN 10: 1107096391
ISBN 13: 9781107096394
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Librería: moluna, Greven, Alemania
Calificación del vendedor: 5 de 5 estrellas
Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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. Nº de ref. del artículo: 447215727
Cantidad disponible: Más de 20 disponibles
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Machine Learning
Publicado por
Cambridge University Press, GB, 2012
ISBN 10: 1107096391
ISBN 13: 9781107096394
Nuevo
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Librería: Rarewaves.com UK, London, Reino Unido
Calificación del vendedor: 5 de 5 estrellas
Hardback. Condición: New. 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: LU-9781107096394
Cantidad disponible: Más de 20 disponibles