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portada Data Science for the Geosciences
Type
Physical Book
Author
Publisher
Language
English
Pages
250
Format
Paperback
Dimensions
25.2 x 20.2 x 1.6 cm
Weight
0.66 kg.
ISBN13
9781009201407
Categories

Data Science for the Geosciences

Jef Caers (Author) · Lijing Wang (Author) · David Zhen Yin (Author) · Cambridge University Press · Paperback

Data Science for the Geosciences - Wang, Lijing ; Yin, David Zhen ; Caers, Jef

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Synopsis "Data Science for the Geosciences"

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.

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