ISBN: 9783031351136 - machine learning for earth sciences: using python to solve geological problems (springer textbooks in earth sciences, geography and environment) (14 resultados)

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.…

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Hardcover. Condición: Brand New. 209 pages. 9.25x6.25x0.75 inches. In Stock.

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Condición: gut. 2023. Machine Learning for Earth Sciences In deutscher Sprache. pages.

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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.…

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.…

Buch. Condición: Neu. nach der Bestellung gedruckt 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.…

Condición: New. Print on Demand.

Buch. Condición: 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.…

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