Data Science for the Geosciences (Paperback). Questo articolo non è disponibile.
Lingua: inglese
Editore: Cambridge University Press, Cambridge, 2023
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Descrizione dell’articolo da parte del venditore
Paperback. 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. An accessible text that provides students and instructors with the data science foundations to address earth science questions using real-world case studies. Focusing on intuitive reasoning, students are encouraged to develop their understanding through exercises utilizing Python notebooks and real datasets. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.…
Codice articolo 9781009201407
- Titolo
- Data Science for the Geosciences (Paperback)
- Autore
- Lijing Wang
- Editore
- Cambridge University Press, Cambridge
- Anno di pubblicazione
- 2023
- Condizione
- new
- Rilegatura
- Paperback
- Lingua
- inglese
- ISBN 10
- 1009201409
- ISBN 13
- 9781009201407
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Informazioni sull’autore
Dr. Zhen Yin is a research scientist and co-founder of the Stanford Mineral-X (https://mineralx.stanford.edu/) at Stanford Doerr School of Sustainability. His research developments in data science have been implemented in various subjects, including Antarctica topographic modeling, critical mineral explorations in Asia/North America/Africa, and North Sea projects. He was previously a Research Associate at the Edinburgh Time-Lapse Project in Scotland, leading a research collaboration with Equinor from 2016 to 2018, and a Postdoctoral Fellow at the Stanford Chevron Center of Research Excellence from 2018 to 2021.
Dr. Jef Caers is Professor of Earth and Planetary Sciences in the Stanford Doerr School of Sustainability. He is the author of a wide range of journal papers across mathematics, statistics, geological sciences, geophysics, engineering and computer science, and four other books. He has received several best paper awards, as well as the 2001 Vistelius Award from the International Association for Mathematical Geosciences (IAMG) and the 2014 Krumbein Medal from the IAMG for his career achievement.
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