Introduction to environmental data science / (Record no. 46749)
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| 000 -LEADER | |
|---|---|
| fixed length control field | 02493cam a22002298i 4500 |
| 005 - DATE AND TIME OF LATEST TRANSACTION | |
| control field | 20250324063035.0 |
| 008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION | |
| fixed length control field | 221214s2023 nyu b 001 0 eng |
| 020 ## - INTERNATIONAL STANDARD BOOK NUMBER | |
| ISBN | 9781107065550 |
| 040 ## - CATALOGING SOURCE | |
| Original cataloging agency | RCL |
| 082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER | |
| Classification number | 363.700285 H89I |
| 100 1# - MAIN ENTRY--PERSONAL NAME | |
| Personal name | Hsieh, William Wei, |
| 245 10 - TITLE STATEMENT | |
| Title | Introduction to environmental data science / |
| Statement of responsibility, etc | William W. Hsieh. |
| 260 ## - PUBLICATION, DISTRIBUTION, ETC. | |
| Place of publication | New York: |
| Name of publisher | Cambridge University Press, |
| Year of publication | 2023. |
| 300 ## - PHYSICAL DESCRIPTION | |
| Number of Pages | xx, 627p. ; 24cm. |
| 504 ## - BIBLIOGRAPHY, ETC. NOTE | |
| Bibliography, etc | Includes bibliographical references and index. |
| 520 ## - SUMMARY, ETC. | |
| Summary, etc | "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"-- |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Environmental sciences |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Environmental protection |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Environmental management |
| 650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM | |
| Topical Term | Machine learning. |
| 942 ## - ADDED ENTRY ELEMENTS (KOHA) | |
| Koha item type | Books |
| Full call number | Accession Number | Lost status | Damaged status | Price effective from | Koha item type | Not for loan | Collection code | Withdrawn status | Home library | Current library | Shelving location | Date acquired | Source of acquisition | Cost, normal purchase price |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 363.700285 H89I | 64961 | 03/24/2025 | Books | Environmental Studies Department Books | RCL | RCL | General Stacks | 03/24/2025 | DDC | 6341.54 | ||||
| 363.700285 H89I | 64962 | 03/24/2025 | Books | Environmental Studies Department Books | RCL | RCL | General Stacks | 03/24/2025 | DDC | 6341.54 |