01569cam a2200205 i 4500001000800000003000900008005001700017008004100034020002500075040001300100041000800113082002200121100003100143245010700174260004300281300006200324520089200386650004801278650003701326TB12827IN-BhIIT20260313154421.0170518s2017    flua          000 0 eng    a9783031351167 (pbk.)  aIN-BhIIT  aeng00a550.285631bPET/M  aPetrelli, MaurizioeAuthor00aMachine learning for earth sciences :busing python to solve geological problems /cMaurizio Petrelli.  aSwitzerland :bSpringer Nature,c2023.  axvi, 209 p. :billustrations, maps (some color) ;c27 cm.  aThis 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. 0aEarth sciencesxComputer network resources. 0aEarth sciencesxData processing.