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Condition: Good. Pages intact with minimal writing/highlighting. The binding may be loose and creased. Dust jackets/supplements are not included. Stock photo provided. Product includes identifying sticker. Better World Books: Buy Books. Do Good.
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Condition: like_new. This book is in Like New condition. It is unused, but has a remainder mark on the edge of the pages. Otherwise it is a new book.
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Probabilistic Machine Learning for Civil Engineers (Mit Press)
Language: English
Published by The MIT Press Bookstore, 2020
ISBN 10: 0262538709 ISBN 13: 9780262538701
Condition: New. pp. 304.
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Probabilistic Machine Learning for Civil Engineers (Paperback)
Language: English
Published by MIT Press Ltd, Cambridge, Mass., 2020
ISBN 10: 0262538709 ISBN 13: 9780262538701
Paperback. Condition: new. Paperback. An introduction to key concepts and techniques in probabilistic machine learning for civil engineering students and professionals; with many step-by-step examples, illustrations, and exercises.This book introduces probabilistic machine learning concepts to civil engineering students and professionals, presenting key approaches and techniques in a way that is accessible to readers without a specialized background in statistics or computer science. It presents different methods clearly and directly, through step-by-step examples, illustrations, and exercises. Having mastered the material, readers will be able to understand the more advanced machine learning literature from which this book draws.The book presents key approaches in the three subfields of probabilistic machine learning- supervised learning, unsupervised learning, and reinforcement learning. It first covers the background knowledge required to understand machine learning, including linear algebra and probability theory. It goes on to present Bayesian estimation, which is behind the formulation of both supervised and unsupervised learning methods, and Markov chain Monte Carlo methods, which enable Bayesian estimation in certain complex cases. The book then covers approaches associated with supervised learning, including regression methods and classification methods, and notions associated with unsupervised learning, including clustering, dimensionality reduction, Bayesian networks, state-space models, and model calibration. Finally, the book introduces fundamental concepts of rational decisions in uncertain contexts and rational decision-making in uncertain and sequential contexts. Building on this, the book describes the basics of reinforcement learning, whereby a virtual agent learns how to make optimal decisions through trial and error while interacting with its environment. An introduction to key concepts and techniques in probabilistic machine learning for civil engineering students and professionals; with many step-by-step examples, illustrations, and exercises. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
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Condition: New.
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Condition: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
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Condition: New. This is a Brand-new US Edition. This Item may be shipped from US or any other country as we have multiple locations worldwide.
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Probabilistic Machine Learning for Civil Engineers (Mit Press)
Language: English
Published by The MIT Press Bookstore, 2020
ISBN 10: 0262538709 ISBN 13: 9780262538701
Condition: New. pp. 304.
-
Paperback. Condition: New.
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Probabilistic Machine Learning for Civil Engineers (Mit Press)
Language: English
Published by The MIT Press Bookstore, 2020
ISBN 10: 0262538709 ISBN 13: 9780262538701
Condition: New. pp. 304.
-
Probabilistic Machine Learning For Civil Engineers The Mit Press
Language: English
Published by Mit Press, 2020
Soft cover. Condition: New. ISBN:9780262538701.
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Condition: As New. Unread book in perfect condition.
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Probabilistic Machine Learning for Civil Engineers
Seller: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Ireland
Seller rating 5 out of 5 stars
Condition: New. 2020. Illustrated. Paperback. . . . . .
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Encuadernación de tapa dura. Condition: Bien. Panamericana, 2006. Ciencias de la Salud, Naturales y Divulgación Científica. Especialidades. Medicina. Patología general. Medicina clínica. Terapéutica. Profusamente ilustrado. 100 páginas aprox. 25 x 18. Tapa dura con sobrecubierta de editorial ilustrada. Sin subrayados. Perfecto estado de conservación. ISBN: 8479033037.
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International EditionPaperback. Condition: New. Brand New! Fast Delivery "International Edition " and ship within 24-48 hours. Deliver by FedEx and Dhl, & Aramex, UPS, & USPS and we do accept APO and PO BOX Addresses. Order can be delivered worldwide within 4-6 Working days .and we do have flat rate for up to 2LB. Extra shipping charges will be requested This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
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Paperback. Condition: Brand New. 269 pages. 9.75x8.00x0.75 inches. In Stock.
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Condition: New. 2020. Illustrated. Paperback. . . . . . Books ship from the US and Ireland.
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Paperback. Condition: New.
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Paperback. Condition: New.
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Probabilistic Machine Learning for Civil Engineers (Paperback)
Language: English
Published by MIT Press Ltd, Cambridge, Mass., 2020
ISBN 10: 0262538709 ISBN 13: 9780262538701
Paperback. Condition: new. Paperback. An introduction to key concepts and techniques in probabilistic machine learning for civil engineering students and professionals; with many step-by-step examples, illustrations, and exercises.This book introduces probabilistic machine learning concepts to civil engineering students and professionals, presenting key approaches and techniques in a way that is accessible to readers without a specialized background in statistics or computer science. It presents different methods clearly and directly, through step-by-step examples, illustrations, and exercises. Having mastered the material, readers will be able to understand the more advanced machine learning literature from which this book draws.The book presents key approaches in the three subfields of probabilistic machine learning- supervised learning, unsupervised learning, and reinforcement learning. It first covers the background knowledge required to understand machine learning, including linear algebra and probability theory. It goes on to present Bayesian estimation, which is behind the formulation of both supervised and unsupervised learning methods, and Markov chain Monte Carlo methods, which enable Bayesian estimation in certain complex cases. The book then covers approaches associated with supervised learning, including regression methods and classification methods, and notions associated with unsupervised learning, including clustering, dimensionality reduction, Bayesian networks, state-space models, and model calibration. Finally, the book introduces fundamental concepts of rational decisions in uncertain contexts and rational decision-making in uncertain and sequential contexts. Building on this, the book describes the basics of reinforcement learning, whereby a virtual agent learns how to make optimal decisions through trial and error while interacting with its environment. An introduction to key concepts and techniques in probabilistic machine learning for civil engineering students and professionals; with many step-by-step examples, illustrations, and exercises. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.
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ProbabilisticMachineLearningforCivilEngineers Format: TradePaperback
Published by Penguin Random House
ISBN 10: 0262538709 ISBN 13: 9780262538701
Condition: As New. Unread copy in mint condition.
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ProbabilisticMachineLearningforCivilEngineers Format: TradePaperback
Published by Penguin Random House
ISBN 10: 0262538709 ISBN 13: 9780262538701
Condition: New. Brand New.
