MARC details
000 -LEADER |
fixed length control field |
03917cam a2200481 i 4500 |
001 - CONTROL NUMBER |
control field |
on1355502288 |
003 - CONTROL NUMBER IDENTIFIER |
control field |
OCoLC |
005 - DATE AND TIME OF LATEST TRANSACTION |
control field |
20240904140220.0 |
008 - FIXED-LENGTH DATA ELEMENTS--GENERAL INFORMATION |
fixed length control field |
221214t20232023nyua b 001 0 eng |
010 ## - LIBRARY OF CONGRESS CONTROL NUMBER |
LC control number |
2022054278 |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
9781107065550 |
Qualifying information |
(hardback) |
020 ## - INTERNATIONAL STANDARD BOOK NUMBER |
International Standard Book Number |
1107065550 |
035 ## - SYSTEM CONTROL NUMBER |
System control number |
(OCoLC)1355502288 |
040 ## - CATALOGING SOURCE |
Original cataloging agency |
DLC |
Language of cataloging |
eng |
Description conventions |
rda |
Transcribing agency |
DLC |
Modifying agency |
OCLCF |
-- |
YDX |
-- |
OCLCO |
-- |
Y@Y |
-- |
CNR |
042 ## - AUTHENTICATION CODE |
Authentication code |
pcc |
049 ## - LOCAL HOLDINGS (OCLC) |
Holding library |
CNRM |
050 00 - LIBRARY OF CONGRESS CALL NUMBER |
Classification number |
GE45.D37 |
Item number |
H74 2023 |
082 00 - DEWEY DECIMAL CLASSIFICATION NUMBER |
Classification number |
363.700285 |
Edition number |
23/eng20221219 |
100 1# - MAIN ENTRY--PERSONAL NAME |
Personal name |
Hsieh, William Wei, |
Dates associated with a name |
1955- |
Relator term |
author |
Affiliation |
University of British Columbia |
245 10 - TITLE STATEMENT |
Title |
Introduction to Environmental Data Science. |
264 #1 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
Place of production, publication, distribution, manufacture |
Cambridge ; |
-- |
New York : |
Name of producer, publisher, distributor, manufacturer |
Cambridge University Press, |
Date of production, publication, distribution, manufacture, or copyright notice |
2023. |
264 #4 - PRODUCTION, PUBLICATION, DISTRIBUTION, MANUFACTURE, AND COPYRIGHT NOTICE |
Date of production, publication, distribution, manufacture, or copyright notice |
2023. |
300 ## - PHYSICAL DESCRIPTION |
Extent |
xx, 627 pages : |
Other physical details |
illustrations ; |
Dimensions |
25 cm |
336 ## - CONTENT TYPE |
Content type term |
text |
Content type code |
txt |
Source |
rdacontent |
337 ## - MEDIA TYPE |
Media type term |
unmediated |
Media type code |
n |
Source |
rdamedia |
338 ## - CARRIER TYPE |
Carrier type term |
volume |
Carrier type code |
nc |
Source |
rdacarrier |
504 ## - BIBLIOGRAPHY, ETC. NOTE |
Bibliography, etc |
Includes bibliographical references and index. |
505 0# - FORMATTED CONTENTS NOTE |
Formatted contents note |
Basics -- Probability distributions -- Statistical inference -- Linear regression -- Neural networks -- Non-linear optimization -- Learning and generalization -- Principal components and canonical correlation -- Unsupervised learning -- Time series -- Classification -- Kernel methods -- Decision trees, random forests and boosting -- Deep learning -- Forecast verification and post-processing -- Merging of machine learning and physics. |
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"-- |
Assigning source |
Provided by publisher. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Environmental sciences |
General subdivision |
Data processing. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Environmental protection |
General subdivision |
Data processing. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Environmental management |
General subdivision |
Data processing. |
650 #0 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Machine learning. |
650 #6 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Sciences de l'environnement |
General subdivision |
Informatique. |
650 #6 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Environnement |
General subdivision |
Protection |
-- |
Informatique. |
650 #6 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Environnement |
General subdivision |
Gestion |
-- |
Informatique. |
650 #6 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Apprentissage automatique. |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Environmental management |
General subdivision |
Data processing |
Source of heading or term |
fast |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Environmental protection |
General subdivision |
Data processing |
Source of heading or term |
fast |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Environmental sciences |
General subdivision |
Data processing |
Source of heading or term |
fast |
650 #7 - SUBJECT ADDED ENTRY--TOPICAL TERM |
Topical term or geographic name as entry element |
Machine learning |
Source of heading or term |
fast |
942 ## - ADDED ENTRY ELEMENTS (KOHA) |
Koha item type |
BOOK |
Source of classification or shelving scheme |
Library of Congress Classification |