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Introduction to Environmental Data Science

By: William W. Hsieh (Author)

Ksh 10,800.00
Format :

Format(s): DRM PDF

ISBN-13: 9781009301800

Publisher: Cambridge University Press

Imprint: Cambridge University Press

Publication Date: March 8th, 2023

Country of Publication: GB

Language: English

Physical Edition EAN: 9781107065550

Category: Data analysis: general , Meteorology & climatology , Geographical information systems (GIS) & remote sensing , The environment , Environmental management , Environmental monitoring , Mathematical & statistical software , Data mining , Machine learning , Pattern recognition

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  • Author Bio

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.

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