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02923aam a2200325 i 4500 001 DFF75D98E97711ED8437380758ECA4DB 003 SILO 005 20230503010033 008 221214s2023 nyua b 001 0 eng 010 $a 2022054278 020 $a 1107065550 020 $a 9781107065550 035 $a (OCoLC)1355502288 040 $a DLC $b eng $e rda $c DLC $d OCLCF $d YDX $d SILO 042 $a pcc 050 00 $a GE45 D37 H74 2023 100 1 $a Hsieh, William Wei, $d 1955- $e author. 245 10 $a Introduction to environmental data science / $c William W. Hsieh. 264 1 $a Cambridge ; $b Cambridge University Press, $c 2023. 300 $a xx, 625 pages : $b illustrations ; $c 25 cm 504 $a Includes bibliographical references and index. 520 $a "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 are 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. William W. Hsieh is a professor emeritus in the Department of Earth, Ocean and Atmospheric Sciences at the University of British Columbia. Known as a pioneer in introducing machine learning to environmental science, he has written over 100 peer-reviewed journal papers on climate variability, machine learning, atmospheric science, oceanography, hydrology and agricultural science. He is the author of the book Machine Learning Methods in the Environmental Sciences (2009, Cambridge University Press), the first single-authored textbook on machine learning for environmental scientists. Currently retired in Victoria, British Columbia, he enjoys growing organic vegetables"-- $c Provided by publisher. 650 0 $a Environmental sciences $x Data processing. 650 0 $a Environmental protection $x Data processing. 650 0 $a Environmental management $x Data processing. 650 0 $a Machine learning. 941 $a 1 952 $l USUX851 $d 20240202030111.0 956 $a http://locator.silo.lib.ia.us/search.cgi?index_0=id&term_0=DFF75D98E97711ED8437380758ECA4DB 994 $a C0 $b IWAInitiate Another SILO Locator Search