Machine Learning for Earth Sciences: Using Python to Solve Geological Problems (Springer Textbooks in Earth Sciences, Geography and Environment) - Hardcover

Buch 49 von 55: Springer Textbooks in Earth Sciences, Geography and Environment

Petrelli, Maurizio

 
9783031351136: Machine Learning for Earth Sciences: Using Python to Solve Geological Problems (Springer Textbooks in Earth Sciences, Geography and Environment)
Hardcover
ISBN 10: 3031351134 ISBN 13: 9783031351136
Verlag: Springer, 2023

Inhaltsangabe

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.

Die Inhaltsangabe kann sich auf eine andere Ausgabe dieses Titels beziehen.

Über die Autorin bzw. den Autor

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. 


Von der hinteren Coverseite

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.

„Über diesen Titel“ kann sich auf eine andere Ausgabe dieses Titels beziehen.

Verlag
Springer
Erscheinungsdatum
2023
Sprache
Englisch
ISBN 10 
3031351134
ISBN 13 
9783031351136
Einband
Gebundene Ausgabe
Anzahl der Seiten
225
Kontakt zum Hersteller
ProductSafety@springernature.com
ProductSafety@springernature.com

Poststr. 9
Darmstadt
64293
Deutschland