悦耳
发表于 2025-3-25 07:21:41
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帐单
发表于 2025-3-25 08:12:05
Textbook 2023ata, 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..
aspersion
发表于 2025-3-25 13:34:21
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外露
发表于 2025-3-25 17:06:17
Machine Learning for Earth Sciences978-3-031-35114-3Series ISSN 2510-1307 Series E-ISSN 2510-1315
祖传财产
发表于 2025-3-25 21:20:07
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背书
发表于 2025-3-26 03:02:34
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暗语
发表于 2025-3-26 04:47:15
https://doi.org/10.1007/978-3-031-35114-3Deep Learning; Application of Machine Learning; Python Tools and Techniques; Tree-Based Models; ML Tools
sundowning
发表于 2025-3-26 11:52:43
Clustering of Multi-Spectral Dataions. It describes how to import, pre-process, describe, and analyze multi-spectral data that can be downloaded from access points such as USGS Earth Explorer, the Copernicus Open Access Hub, and Theia.
FRET
发表于 2025-3-26 12:54:16
Introduction to Machine LearningThis chapter introduces the basics of machine learning to geologists. Toward this end, it first provides fundamental definitions and introduces common terminology. It then discusses the learning process and defines the different types of learning paradigms (i.e., supervised, unsupervised, and semisupervised).
spondylosis
发表于 2025-3-26 18:30:20
Setting Up Your Python Environments for Machine LearningThis chapter details how to prepare a Python environment to start working with Machine Learning in Earth Sciences. First, it shows how to set up a local Python environment, and then how to create a remote Linux instance. Finally, it explains how to start working with cloud-based machine learning environments.