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Machine Learning for Earth Sciences: Using Python to Solve Geological Problems (Springer Textbooks in Earth Sciences, Geography and Environment) - Tapa dura
Sinopsis
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.
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Acerca del 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.
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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.
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Machine Learning for Earth Sciences
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Springer-Verlag, 2023
ISBN 10: 3031351134
ISBN 13: 9783031351136
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Condición: Wie Neu. Zustandsbeschreibung: leichte Lagerspuren, Rücken minimal bestoßen/minor shelfwear, spine minimally bumped. Using Python to Solve Geological Problems. XVI,209 Seiten mit 99 Farb- und drei s/w-Abb., gebunden (Springer Textbooks in Earth Sciences, Geography and Environment/Springer-Verlag 2023). Statt EUR 85,59. Gewicht: 507 g - Gebunden/Gebundene Ausgabe - Sprache: Englisch. Nº de ref. del artículo: 116661
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Machine Learning for Earth Sciences
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ISBN 10: 3031351134
ISBN 13: 9783031351136
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Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. 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. Nº de ref. del artículo: 870565853
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Machine Learning for Earth Sciences: Using Python to Solve Geological Problems (Springer Textbooks in Earth Sciences, Geography and Environment)
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Machine Learning for Earth Sciences
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ISBN 10: 3031351134
ISBN 13: 9783031351136
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Buch. Condición: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -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. 228 pp. Englisch. Nº de ref. del artículo: 9783031351136
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Machine Learning for Earth Sciences: Using Python to Solve Geological Problems (Springer Textbooks in Earth Sciences, Geography and Environment)
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Machine Learning for Earth Sciences : Using Python to Solve Geological Problems
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ISBN 10: 3031351134
ISBN 13: 9783031351136
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Buch. Condición: Neu. Druck auf Anfrage Neuware - Printed after ordering - 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. Nº de ref. del artículo: 9783031351136
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Machine Learning for Earth Sciences: Using Python to Solve Geological Problems (Springer Textbooks in Earth Sciences, Geography and Environment)
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Machine Learning for Earth Sciences
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Springer International Publishing, Springer Nature Switzerland Sep 2023, 2023
ISBN 10: 3031351134
ISBN 13: 9783031351136
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Buch. Condición: Neu. Neuware -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.Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg 228 pp. Englisch. Nº de ref. del artículo: 9783031351136
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Machine Learning for Earth Sciences: Using Python to Solve Geological Problems
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Hardcover. Condición: Brand New. 209 pages. 9.25x6.25x0.75 inches. In Stock. Nº de ref. del artículo: x-3031351134
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