William W. Hsieh (Vancouver University of British Columbia)

Introduction to Environmental Data Science

• Gebundenes Buch

Produktbeschreibung

This book provides a comprehensive guide to machine learning and statistics for students and researchers of environmental data science. A broad range of methods are covered together with the relevant background mathematics. End-of-chapter exercises and online data sets are included.

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Produktdetails

• Verlag: Cambridge University Press
• Seitenzahl: 647
• Erscheinungstermin: 23. März 2023
• Englisch
• Abmessung: 248mm x 175mm x 35mm
• Gewicht: 1328g
• ISBN-13: 9781107065550
• ISBN-10: 1107065550
• Artikelnr.: 64775941

Autorenporträt

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 ( Cambridge University Press, 2009), the first single-authored textbook on machine learning for environmental scientists. Currently retired in Victoria, British Columbia, he enjoys growing organic vegetables.

Inhaltsangabe

1. Introduction
2. Basics
3. Probability distributions
4. Statistical inference
5. Linear regression
6. Neural networks
7. Nonlinear optimization
8. Learning and generalization
9. Principal components and canonical correlation
10. Unsupervised learning
11. Time series
12. Classification
13. Kernel methods
14. Decision trees, random forests and boosting
15. Deep learning
16. Forecast verification and post-processing
17. Merging of machine learning and physics
Appendices
References
Index.