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Cover: 9781107065550 | Introduction to Environmental Data Science | William W. Hsieh | Buch
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Introduction to Environmental Data Science
Buch von William W. Hsieh
Sprache: Englisch

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Beschreibung
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.
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.
Über den Autor
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.
Inhaltsverzeichnis
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.
Details
Erscheinungsjahr: 2023
Fachbereich: Kommunikationswissenschaften
Genre: Medienwissenschaften
Rubrik: Wissenschaften
Medium: Buch
Seiten: 647
Inhalt: Gebunden
ISBN-13: 9781107065550
ISBN-10: 1107065550
Sprache: Englisch
Einband: Gebunden
Autor: Hsieh, William W.
Hersteller: Cambridge University Press
Maße: 248 x 175 x 35 mm
Von/Mit: William W. Hsieh
Erscheinungsdatum: 23.03.2023
Gewicht: 1,328 kg
preigu-id: 122748879
Über den Autor
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.
Inhaltsverzeichnis
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.
Details
Erscheinungsjahr: 2023
Fachbereich: Kommunikationswissenschaften
Genre: Medienwissenschaften
Rubrik: Wissenschaften
Medium: Buch
Seiten: 647
Inhalt: Gebunden
ISBN-13: 9781107065550
ISBN-10: 1107065550
Sprache: Englisch
Einband: Gebunden
Autor: Hsieh, William W.
Hersteller: Cambridge University Press
Maße: 248 x 175 x 35 mm
Von/Mit: William W. Hsieh
Erscheinungsdatum: 23.03.2023
Gewicht: 1,328 kg
preigu-id: 122748879
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