Verlag: Cambridge University Press, 2009
ISBN 10: 0521884381 ISBN 13: 9780521884389
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: Like New. First Edition. A firm, square and tight hardback with strong joints, just showing a few very minor hardly noticeable bumps and some mild cosmetic wear. Hence a non-text page is stamped 'damaged'. Despite such this book is actually in nearly new condition. Thus the contents are crisp, fresh and clean with no pen-marks. Not from a library so no such stamps or labels. Now offered for sale at a very reasonable price.
Verlag: Cambridge University Press, 2009
ISBN 10: 0521884381 ISBN 13: 9780521884389
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: Good. 1st Edition. Some underlining in pencil until page 21. (Could be erased if one desired). Free or markings after that. Cover looks great with minimal wear. ***Shipped within 24 hours from the beautiful Baltimore inner harbor area. First class service. Most items packed in boxes, not envelopes.***. Book.
Verlag: Cambridge University Press, 2009
ISBN 10: 0521884381 ISBN 13: 9780521884389
Sprache: Englisch
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In den Warenkorbhardcover. Zustand: Very Good. Pages are crisp and clean, no marking. Cover is verygood. Binding is tight/good.
Verlag: Cambridge University Press, 2014
ISBN 10: 1107678420 ISBN 13: 9781107678422
Sprache: Englisch
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ISBN 10: 1107678420 ISBN 13: 9781107678422
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In den WarenkorbZustand: New. pp. 562 246 Illus.
Verlag: Cambridge University Press, 2014
ISBN 10: 1107678420 ISBN 13: 9781107678422
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In den WarenkorbTaschenbuch. Zustand: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book introduces the formal foundations and practical applications of Bayesian networks.
Verlag: Cambridge University Press, Cambridge, 2014
ISBN 10: 1107678420 ISBN 13: 9781107678422
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In den WarenkorbPaperback. Zustand: new. Paperback. This book is a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis. It also treats exact and approximate inference algorithms at both theoretical and practical levels. The treatment of exact algorithms covers the main inference paradigms based on elimination and conditioning and includes advanced methods for compiling Bayesian networks, time-space tradeoffs, and exploiting local structure of massively connected networks. The treatment of approximate algorithms covers the main inference paradigms based on sampling and optimization and includes influential algorithms such as importance sampling, MCMC, and belief propagation. The author assumes very little background on the covered subjects, supplying in-depth discussions for theoretically inclined readers and enough practical details to provide an algorithmic cookbook for the system developer. This book provides a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Verlag: Cambridge University Press, 2014
ISBN 10: 1107678420 ISBN 13: 9781107678422
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In den WarenkorbZustand: 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.
Verlag: Cambridge University Press, 2009
ISBN 10: 0521884381 ISBN 13: 9780521884389
Sprache: Englisch
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In den Warenkorbhardcover. Zustand: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Verlag: Cambridge University Press, 2009
ISBN 10: 0521884381 ISBN 13: 9780521884389
Sprache: Englisch
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In den WarenkorbHardcover. Zustand: new. Excellent Condition.Excels in customer satisfaction, prompt replies, and quality checks.
Verlag: Cambridge University Press, 2014
ISBN 10: 1107678420 ISBN 13: 9781107678422
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: Good. Connecting readers with great books since 1972! Used textbooks may not include companion materials such as access codes, etc. May have some wear or writing/highlighting. We ship orders daily and Customer Service is our top priority!
Verlag: Cambridge University Press, 2009
ISBN 10: 0521884381 ISBN 13: 9780521884389
Sprache: Englisch
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Verlag: Cambridge University Press, 2009
ISBN 10: 0521884381 ISBN 13: 9780521884389
Sprache: Englisch
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In den Warenkorbhardcover. Zustand: New. In shrink wrap. Looks like an interesting title!
Verlag: Cambridge University Press, 2014
ISBN 10: 1107678420 ISBN 13: 9781107678422
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: new. Paperback. This book is a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis. It also treats exact and approximate inference algorithms at both theoretical and practical levels. The treatment of exact algorithms covers the main inference paradigms based on elimination and conditioning and includes advanced methods for compiling Bayesian networks, time-space tradeoffs, and exploiting local structure of massively connected networks. The treatment of approximate algorithms covers the main inference paradigms based on sampling and optimization and includes influential algorithms such as importance sampling, MCMC, and belief propagation. The author assumes very little background on the covered subjects, supplying in-depth discussions for theoretically inclined readers and enough practical details to provide an algorithmic cookbook for the system developer. This book provides a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
Verlag: Cambridge University Press, 2009
ISBN 10: 0521884381 ISBN 13: 9780521884389
Sprache: Englisch
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In den WarenkorbPaperback. Zustand: new. Paperback. This book is a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis. It also treats exact and approximate inference algorithms at both theoretical and practical levels. The treatment of exact algorithms covers the main inference paradigms based on elimination and conditioning and includes advanced methods for compiling Bayesian networks, time-space tradeoffs, and exploiting local structure of massively connected networks. The treatment of approximate algorithms covers the main inference paradigms based on sampling and optimization and includes influential algorithms such as importance sampling, MCMC, and belief propagation. The author assumes very little background on the covered subjects, supplying in-depth discussions for theoretically inclined readers and enough practical details to provide an algorithmic cookbook for the system developer. This book provides a thorough introduction to the formal foundations and practical applications of Bayesian networks. It provides an extensive discussion of techniques for building Bayesian networks that model real-world situations, including techniques for synthesizing models from design, learning models from data, and debugging models using sensitivity analysis. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Verlag: Cambridge University Press, 2014
ISBN 10: 1107678420 ISBN 13: 9781107678422
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Verlag: Cambridge University Press, 2009
ISBN 10: 0521884381 ISBN 13: 9780521884389
Sprache: Englisch
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ISBN 10: 1107678420 ISBN 13: 9781107678422
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