
Machine Learning for Earth Sciences by Maurizio Petrelli
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.-
Data Assimilation Fundamentals
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Collecting, Processing and Presenting Geoscientific Information
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Isotopes and the Natural Environment
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Principles of Karst Hydrogeology
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Hydrothermal Ore Deposits: Geochemical Attributes
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Geoarchaeology
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Physical Geodesy
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Micrometeorological Measurements
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Mineral Resources
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Elements and Mineral Resources
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Python Recipes for Earth Sciences
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Atmospheres and Oceans on Computers
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An Introduction to Fluid Mechanics
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Introduction to Python in Earth Science Data Analysis
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Fission-Track Thermochronology and its Application to Geology
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Geophysical Fluid Dynamics I
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Geophysics of the Cryosphere
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Thermodynamics in Earth and Planetary Sciences
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Geophysical Fluid Dynamics II
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Ocean Acoustics
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Glaciers and Ice Sheets in the Climate System
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A Geographer's Guide to Computing Fundamentals
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Crystallography
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Governance of Radioactive Waste, Special Waste and Carbon Storage
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Data Science for Transport
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Handling of Geospatial Data with QGIS
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Cartography
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R Applications in Earth Sciences
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Transmitted Light Microscopy of Rock-Forming Minerals
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Introduction to Geophysics
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.
| SKU | Unavailable |
| ISBN 13 | 9783031351167 |
| Title | Machine Learning for Earth Sciences |
| Author | Maurizio Petrelli |
| Series | Springer Textbooks In Earth Sciences Geography And Environment |
| Condition | Unavailable |
| Binding Type | Paperback |
| Publisher | Springer International Publishing AG |
| Year published | 2024-09-24 |
| Number of pages | 209 |
| Cover note | Book picture is for illustrative purposes only, actual binding, cover or edition may vary. |
| Note | Unavailable |





























