Synopsis
A graduate textbook that provides a unified treatment of machine learning methods and their applications in the environmental sciences.
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About the Author
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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Machine Learning Methods in the Environmental Sciences: Neural Networks and Kernels
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Machine Learning Methods in the Environmental Sciences: Neural Networks and Kernels
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Machine Learning Methods In The Environmental Sciences
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Machine Learning Methods In The Environmental Sciences
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