Machine Learning for Earth Sciences by Maurizio Petrelli

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Summary

This textbook introduces the reader to Machine Learning (ML) applications in Earth Sciences. It describes the main Python tools devoted to ML, the typical workflow of ML applications in Earth Sciences, and proceeds with reporting how ML algorithms work.

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Machine Learning for Earth Sciences by Maurizio Petrelli

This textbook introduces the reader to Machine Learning (ML) applications in Earth Sciences. In detail, it starts by describing the basics of machine learning and its potentials in Earth Sciences to solve geological problems. It describes the main Python tools devoted to ML, the typical workflow of ML applications in Earth Sciences, and proceeds with reporting how ML algorithms work. The book provides many examples of ML application to Earth Sciences problems in many fields, such as the clustering and dimensionality reduction in petro-volcanological studies, the clustering of multi-spectral data, well-log data facies classification, and machine learning regression in petrology. Also, the book introduces the basics of parallel computing and how to scale ML models in the cloud. The book is devoted to Earth Scientists, at any level, from students to academics and professionals.
“This book is essential for anyone planning to apply machine learning to earth science data (including multispectral and hyperspectral imaging)For maximum benefit, the reader should treat it as both an extensive tutorial as well as a bibliography: be prepared to code along with the examples and to look up the references.” (Creed Jones, Computing Reviews, January 1, 2024)

Maurizio Petrelli is an associate professor in petrology and volcanology at the Department of Physics and Geology, University of Perugia. In 2001, he graduated in Geology and obtained his Ph.D. in February 2006 at the University of Perugia. His current studies are focused on the petrological, volcanological, and geochemical characterization of magmatic systems with particular emphasis on time-scales estimates of magmatic processes. He combines the use of numerical simulations, experimental petrology, and the study of natural samples. Since 2016, he has developed a new line of research at the Department of Physics and Geology (University of Perugia) focused on the application of Machine Learning techniques to petrological and volcanological studies. 


SKU Unavailable
ISBN 13 9783031351167
Title Machine Learning for Earth Sciences
Author Maurizio Petrelli
Series Springer Textbooks In Earth Sciences Geography And Environment
Condition Unavailable
Binding Type Paperback
Publisher Springer International Publishing AG
Year published 2024-09-24
Number of pages 209
Cover note Book picture is for illustrative purposes only, actual binding, cover or edition may vary.