Edité par Cambridge University Press, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
Langue: anglais
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Ajouter au panierhardcover. Etat : Very Good. Cover and edges may have some wear.
Edité par Cambridge University Press, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
Langue: anglais
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Ajouter au panierHRD. Etat : New. New Book. Shipped from UK. Established seller since 2000.
Edité par Cambridge University Press, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
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Edité par Cambridge University Press, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
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Edité par Cambridge University Press, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
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Edité par Cambridge University Press, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
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Edité par Cambridge University Press, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
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Edité par Cambridge University Press, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
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Edité par Cambridge University Press, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
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Ajouter au panierEtat : New. 2023. New. hardcover. . . . . .
Edité par Cambridge University Press, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
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Ajouter au panierEtat : New. Über den AutorWilliam W. Hsieh is a professor emeritus in the Department of Earth, Ocean and Atmospheric Sciences at the University of British Columbia. Known as a pioneer in introducing machine learning to environmental science, he.
Edité par Cambridge University Press, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
Langue: anglais
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Ajouter au panierHardcover. Etat : Brand New. 500 pages. 9.69x6.69x1.34 inches. In Stock.
Edité par Cambridge University Press, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
Langue: anglais
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Ajouter au panierEtat : As New. Unread book in perfect condition.
Edité par Cambridge University Press, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
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Edité par Cambridge University Press, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
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Ajouter au panierEtat : New.
Edité par Cambridge University Press Mär 2023, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
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Ajouter au panierBuch. Etat : Neu. Neuware - This book provides a comprehensive guide to machine learning and statistics for students and researchers of environmental data science. A broad range of methods are covered together with the relevant background mathematics. End-of-chapter exercises and online data sets are included.
Edité par Cambridge University Press, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
Langue: anglais
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Ajouter au panierEtat : New. 2023. New. hardcover. . . . . . Books ship from the US and Ireland.
Edité par Cambridge University Press, Cambridge, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
Langue: anglais
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EUR 85,39
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Ajouter au panierHardcover. Etat : new. Hardcover. Statistical and machine learning methods have many applications in the environmental sciences, including prediction and data analysis in meteorology, hydrology and oceanography; pattern recognition for satellite images from remote sensing; management of agriculture and forests; assessment of climate change; and much more. With rapid advances in machine learning in the last decade, this book provides an urgently needed, comprehensive guide to machine learning and statistics for students and researchers interested in environmental data science. It includes intuitive explanations covering the relevant background mathematics, with examples drawn from the environmental sciences. A broad range of topics is covered, including correlation, regression, classification, clustering, neural networks, random forests, boosting, kernel methods, evolutionary algorithms and deep learning, as well as the recent merging of machine learning and physics. Endofchapter exercises allow readers to develop their problem-solving skills, and online datasets allow readers to practise analysis of real data. This book provides a comprehensive guide to machine learning and statistics for students and researchers of environmental data science. A broad range of methods are covered together with the relevant background mathematics. End-of-chapter exercises and online data sets are included. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Edité par CAMBRIDGE UNIVERSITY PRESS, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
Langue: anglais
Vendeur : UK BOOKS STORE, London, LONDO, Royaume-Uni
EUR 120,53
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Ajouter au panierHardcover. Etat : NEW. Brand New! Fast Delivery USA 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 7-14 days and we do have flat rate for up to 2LB. Extra shipping charges will be requested if the Book weight is more than 5 LB. This Item May be shipped from India, United states & United Kingdom. Depending on your location and availability.
Edité par CAMBRIDGE UNIVERSITY PRESS, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
Langue: anglais
Vendeur : URW Books Store, CASPER, WY, Etats-Unis
EUR 120,45
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Ajouter au panierHardcover. Etat : Brand New. Brand New! Fast Delivery, Delivery With In 8-14 working Day Only , USA Edition Original Edition. Excellent Quality, Printing In English Language, Quick delivery by FEDEX & DHL. USPS & UPS Act. Our courier service is not available at PO BOX& APO BOX. Ship from India & United States.
Edité par Cambridge University Press, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
Langue: anglais
Vendeur : Revaluation Books, Exeter, Royaume-Uni
EUR 123,99
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Ajouter au panierHardcover. Etat : Brand New. 500 pages. 9.69x6.69x1.34 inches. In Stock.
Edité par Cambridge University Press, Cambridge, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
Langue: anglais
Vendeur : Grand Eagle Retail, Fairfield, OH, Etats-Unis
EUR 93,59
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Ajouter au panierHardcover. Etat : new. Hardcover. Statistical and machine learning methods have many applications in the environmental sciences, including prediction and data analysis in meteorology, hydrology and oceanography; pattern recognition for satellite images from remote sensing; management of agriculture and forests; assessment of climate change; and much more. With rapid advances in machine learning in the last decade, this book provides an urgently needed, comprehensive guide to machine learning and statistics for students and researchers interested in environmental data science. It includes intuitive explanations covering the relevant background mathematics, with examples drawn from the environmental sciences. A broad range of topics is covered, including correlation, regression, classification, clustering, neural networks, random forests, boosting, kernel methods, evolutionary algorithms and deep learning, as well as the recent merging of machine learning and physics. Endofchapter exercises allow readers to develop their problem-solving skills, and online datasets allow readers to practise analysis of real data. This book provides a comprehensive guide to machine learning and statistics for students and researchers of environmental data science. A broad range of methods are covered together with the relevant background mathematics. End-of-chapter exercises and online data sets are included. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Edité par Cambridge University Press, Cambridge, 2023
ISBN 10 : 1107065550 ISBN 13 : 9781107065550
Langue: anglais
Vendeur : AussieBookSeller, Truganina, VIC, Australie
EUR 147,71
Autre deviseQuantité disponible : 1 disponible(s)
Ajouter au panierHardcover. Etat : new. Hardcover. Statistical and machine learning methods have many applications in the environmental sciences, including prediction and data analysis in meteorology, hydrology and oceanography; pattern recognition for satellite images from remote sensing; management of agriculture and forests; assessment of climate change; and much more. With rapid advances in machine learning in the last decade, this book provides an urgently needed, comprehensive guide to machine learning and statistics for students and researchers interested in environmental data science. It includes intuitive explanations covering the relevant background mathematics, with examples drawn from the environmental sciences. A broad range of topics is covered, including correlation, regression, classification, clustering, neural networks, random forests, boosting, kernel methods, evolutionary algorithms and deep learning, as well as the recent merging of machine learning and physics. Endofchapter exercises allow readers to develop their problem-solving skills, and online datasets allow readers to practise analysis of real data. This book provides a comprehensive guide to machine learning and statistics for students and researchers of environmental data science. A broad range of methods are covered together with the relevant background mathematics. End-of-chapter exercises and online data sets are included. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.