Principal Component Analyses (PCA) for low dimensional representation of material structure

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En provenance du cours de Georgia Institute of Technology
Materials Data Sciences and Informatics
66 notes
Georgia Institute of Technology
66 notes
À partir de la leçon
Materials Knowledge Improvement Cycles
• Learn material structure and its digital representation • Learn how to calculate 2-point statistics • Learn how Principal Component Analysis can be used to reduce dimensionality • Understand Homogenization and Localization concepts

Rencontrer les enseignants

  • Dr. Surya Kalidindi
    Dr. Surya Kalidindi
    Professor
    The George W. Woodruff School of Mechanical Engineering

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