Machine learning methods are used in various fields in environmental sciences today. This is the first single-authored textbook providing a unified treatment of these methods and their applications, and is a valuable resource for advanced undergraduates, graduates, and researchers and practitioners interested in applying such methods to their own work.

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William W. Hsieh is a Professor in the Department of Earth and Ocean Sciences and in the Department of Physics and Astronomy, as well as Chair of the Atmospheric Science Programme, at the University of British Columbia. He is internationally known for his pioneering work in developing and applying machine learning methods in environmental sciences. He has published over eighty peer-reviewed journal publications covering areas of climate variability, machine learning, oceanography, atmospheric science and hydrology.

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