Anbieter: Books Puddle, New York, NY, USA
Zustand: New. pp. 304.
Zustand: Good. Used book that is in clean, average condition without any missing pages.
Verlag: MIT Press Ltd, Cambridge, Mass., 2020
ISBN 10: 0262538709 ISBN 13: 9780262538701
Sprache: Englisch
Anbieter: Grand Eagle Retail, Bensenville, IL, USA
Paperback. Zustand: 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.
Zustand: Brand New. New. US edition. Expediting shipping for all USA and Europe orders excluding PO Box. Excellent Customer Service.
Anbieter: Romtrade Corp., STERLING HEIGHTS, MI, USA
Zustand: 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.
Anbieter: Majestic Books, Hounslow, Vereinigtes Königreich
EUR 50,90
Anzahl: 4 verfügbar
In den WarenkorbZustand: New. pp. 304.
Zustand: New.
Anbieter: Biblios, Frankfurt am main, HESSE, Deutschland
Zustand: New. pp. 304.
Verlag: Mit Press, 2020
Sprache: Englisch
Anbieter: Books in my Basket, New Delhi, Indien
Soft cover. Zustand: New. ISBN:9780262538701.
EUR 63,66
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In den WarenkorbPaperback. Zustand: New.
Zustand: As New. Unread book in perfect condition.
Anbieter: Kennys Bookshop and Art Galleries Ltd., Galway, GY, Irland
Zustand: New. 2020. Illustrated. Paperback. . . . . .
Anbieter: Revaluation Books, Exeter, Vereinigtes Königreich
EUR 78,11
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In den WarenkorbPaperback. Zustand: Brand New. 269 pages. 9.75x8.00x0.75 inches. In Stock.
Zustand: New. 2020. Illustrated. Paperback. . . . . . Books ship from the US and Ireland.
EUR 65,82
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In den WarenkorbPaperback. Zustand: New.
Verlag: MIT Press Ltd, Cambridge, Mass., 2020
ISBN 10: 0262538709 ISBN 13: 9780262538701
Sprache: Englisch
Anbieter: AussieBookSeller, Truganina, VIC, Australien
Paperback. Zustand: 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.
Anbieter: Rarewaves.com UK, London, Vereinigtes Königreich
EUR 63,47
Anzahl: Mehr als 20 verfügbar
In den WarenkorbPaperback. Zustand: New.