Introduction to Environmental Data Science

ISBN-13: 9781107065550 / Twarda / 2023 / 500 str.

Vancouver) Hsieh William W. (University of British Columbia

Opis

A comprehensive guide to machine learning and statistics for students and researchers of environmental data science.

Recenzje

'There is a need for a forward-looking text on environmental data science and William Hsieh's text succeeds in filling the gap. This comprehensive text covers basic to advanced material ranging from timeless statistical techniques to some of the latest machine learning approaches. His refreshingly engaging style is written to be understood and complemented by a plethora of expressive visuals. Hsieh's treatment of nonlinearity is cutting-edge and the final chapter examines ways to combine machine learning with physics. This text is destined to become a modern classic.' Sue Ellen Haupt, National Center for Atmospheric Research

Spis treści

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.