无价值
发表于 2025-3-27 00:20:40
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顾客
发表于 2025-3-27 04:58:48
Unsupervised Machine Learning MethodsThis chapter introduces unsupervised machine learning methods. It starts by describing the algorithms for dimensionality reduction, which include principal component analysis and manifold learning. It then describes clustering methods, such as hierarchical clustering, DBSCAN, mean shift, K-means, spectral clustering, and Gaussian-mixture models.
大气层
发表于 2025-3-27 07:52:46
Clustering and Dimensionality Reduction in PetrologyChapter . describes how to apply unsupervised machine learning methods in petrology. It focuses on analyzing the clinopyroxene erupted by Mt. Etna during the sequence of lava fountains that occurred between February and April of 2021. The application of clustering and dimensionality reduction techniques is described in detail.
北京人起源
发表于 2025-3-27 13:13:02
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恫吓
发表于 2025-3-27 17:10:48
Classification of Well Log Data Facies by Machine LearningThis chapter focuses on the classification by machine learning of facies in well-log data. It progressively develops a machine learning workflow that includes descriptive statistics, algorithm selection, model optimization, model training, and application to blind observations. Each step is discussed in detail.
engagement
发表于 2025-3-27 18:47:53
Machine Learning Regression in PetrologyThis chapter applies machine-learning regression to petrology. It explains how to calibrate machine-learning thermo-barometers based on orthopyroxene crystals in equilibrium with the melt in a volcanic plumbing system. It also describes the calibration of a thermo-barometer based on orthopyroxenes crystals.
BULLY
发表于 2025-3-27 22:35:57
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DNR215
发表于 2025-3-28 02:22:22
Scale Your Models in the CloudThis chapter shows how to scale machine-learning models in the cloud. In the context of cloud computing, the term “scaling” refers to the ability to quickly and efficiently change the capability of a computational resource to handle a model that no longer fits the available resources.
obstruct
发表于 2025-3-28 06:29:41
Introduction to Deep LearningThis chapter is about deep learning. It starts by introducing the basics of deep learning and then introduces PyTorch, a Python deep learning library. It also describes how to set up and train feedforward networks. Finally, it provides an example application dealing with deep learning potentials in the Earth Sciences.
COMA
发表于 2025-3-28 13:47:44
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