Introduction to Environmental Data Science (Hardcover)

William W. Hsieh

ISBN 10: 1107065550 / ISBN 13: 9781107065550

Published by Cambridge University Press, Cambridge, 2023

About this Item

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. Seller Inventory # 9781107065550

Bibliographic Details

Title: Introduction to Environmental Data Science (...

Publisher: Cambridge University Press, Cambridge

Publication Date: 2023

Binding: Hardcover

Condition: new