Synopsis
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.
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l'auteur
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.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Machine Learning for Earth Sciences (eng)
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Machine Learning for Earth Sciences (Paperback)
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ISBN 10 : 3031351169
ISBN 13 : 9783031351167
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Paperback. Etat : new. Paperback. 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 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. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. N° de réf. du vendeur 9783031351167
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Machine Learning for Earth Sciences
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ISBN 10 : 3031351169
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Taschenbuch. Etat : 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. 209 pp. Englisch. N° de réf. du vendeur 9783031351167
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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 (Springer Textbooks in Earth Sciences, Geography and Environment)
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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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Machine Learning for Earth Sciences
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Springer, Palgrave Macmillan Sep 2024, 2024
ISBN 10 : 3031351169
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Taschenbuch. Etat : Neu. This item is printed on demand - Print on Demand Titel. 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 KG, Sachsenplatz 4-6, 1201 Wien 228 pp. Englisch. N° de réf. du vendeur 9783031351167
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Machine Learning for Earth Sciences : Using Python to Solve Geological Problems
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ISBN 10 : 3031351169
ISBN 13 : 9783031351167
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Taschenbuch. Etat : 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. N° de réf. du vendeur 9783031351167
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Machine Learning for Earth Sciences | Using Python to Solve Geological Problems
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Taschenbuch. Etat : Neu. Machine Learning for Earth Sciences | Using Python to Solve Geological Problems | Maurizio Petrelli | Taschenbuch | xvi | Englisch | 2024 | Springer | EAN 9783031351167 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. N° de réf. du vendeur 130115334
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