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Lijing Wang David Zhen Yin Jef Caers Data Science for the Geosciences (Hardback)

C $269.74
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eBay item number:336017789237
Last updated on Jun 17, 2025 07:52:12 EDTView all revisionsView all revisions

Item specifics

Condition
Brand New: A new, unread, unused book in perfect condition with no missing or damaged pages. See the ...
Book Title
Data Science for the Geosciences
Publication Name
Data Science for the Geosciences
Title
Data Science for the Geosciences
Author
Jef Caers
Format
Hardback
EAN
9781009201414
ISBN
9781009201414
Publisher
Cambridge University Press
Genre
Language & Reference
Topic
Computing & Internet
Release Year
2023
Release Date
17/08/2023
Language
English
Country/Region of Manufacture
GB
Item Height
260mm
Item Length
206mm
Item Width
20mm
Item Weight
840g

About this product

Product Identifiers

Publisher
Cambridge University Press
ISBN-10
1009201417
ISBN-13
9781009201414
eBay Product ID (ePID)
10059037164

Product Key Features

Book Title
Data Science for the Geosciences
Number of Pages
250 Pages
Language
English
Topic
Earth Sciences / General
Publication Year
2023
Illustrator
Yes
Genre
Science
Author
Jef Caers, David Zhen Yin, Lijing Wang
Format
Hardcover

Dimensions

Item Height
0.8 in
Item Length
10.2 in
Item Width
8.1 in

Additional Product Features

LCCN
2023-000678
Dewey Edition
23
Reviews
'Literacy in data science and machine learning methods is a necessity for the modern geoscientist. This is an accessible yet thorough overview of key data science topics and their applications. It uses real-world case studies from a variety of geoscientific disciplines and is a valuable resource for students, practitioners, and instructors alike.' Emma Mackie, University of Florida, 'This condensate of essential notions to deal with data typically found in geoscience offers a great toolbox for students who must perform analysis of big data that are spatially distributed or multivariate, or for the estimation of extreme events.' Grégoire Mariethoz, University of Lausanne
Dewey Decimal
550.285
Table Of Content
1. Extreme value statistics; 2. Multi-variate analysis; 3. Spatial data aggregation; 4. Geostatistics; 5. Review of mathematical and statistical concepts.
Synopsis
An accessible text that provides students and instructors with the data science foundations to address earth science questions using real-world case studies. Focusing on intuitive reasoning, students are encouraged to develop their understanding through exercises utilizing Python notebooks and real datasets., Data Science for the Geosciences provides students and instructors with the statistical and machine learning foundations to address Earth science questions using real-world case studies in natural hazards, climate change, environmental contamination and Earth resources. It focuses on techniques that address common characteristics of geoscientific data, including extremes, multivariate, compositional, geospatial and space-time methods. Step-by-step instructions are provided, enabling readers to easily follow the protocols for each method, solve their geoscientific problems and make interpretations. With an emphasis on intuitive reasoning throughout, students are encouraged to develop their understanding without the need for complex mathematics, making this the perfect text for those with limited mathematical or coding experience. Students can test their skills with homework exercises that focus on data scientific analysis, modeling, and prediction problems, and through the use of supplemental Python notebooks that can be applied to real datasets worldwide.
LC Classification Number
QE33.2.S82

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