Introduction to environmental data science / William W. Hsieh.

Format:

Book

Author/Creator:

Hsieh, William Wei, 1955- author.

Language:

English

Subjects (All):

Environmental sciences--Data processing.

Environmental sciences.

Environmental protection--Data processing.

Environmental protection.

Environmental management--Data processing.

Environmental management.

Machine learning.

Physical Description:

1 online resource (xx, 627 pages) : digital, PDF file(s).

Edition:

First edition.

Place of Publication:

Cambridge : Cambridge University Press, 2023.

Summary:

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. End‑of‑chapter exercises allow readers to develop their problem-solving skills, and online datasets allow readers to practise analysis of real data.

Notes:

Title from publisher's bibliographic system (viewed on 23 Mar 2023).

Includes bibliographical references and index.

ISBN:

9781009301800

1009301802

9781107588493

1107588499