Data Science for the Geosciences Paperback / softback
by Lijing (Stanford University, California) Wang, David Zhen (Stanford University, California) Yin, Jef (Stanford University, California) Caers
Paperback / softback
Description
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.
Information
-
Less than 10 available - usually despatched within 24 hours
- Format:Paperback / softback
- Pages:250 pages, Worked examples or Exercises
- Publisher:Cambridge University Press
- Publication Date:17/08/2023
- Category:
- ISBN:9781009201407
Information
-
Less than 10 available - usually despatched within 24 hours
- Format:Paperback / softback
- Pages:250 pages, Worked examples or Exercises
- Publisher:Cambridge University Press
- Publication Date:17/08/2023
- Category:
- ISBN:9781009201407
