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Dimensionality Reduction: Principal Component Analysis and Multidimensional Scaling - Lecture 21

UofU Data Science via YouTube

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Learn about key dimensionality reduction techniques in this university lecture focusing on Principal Component Analysis (PCA) and Multidimensional Scaling (MDS), exploring how these methods help simplify complex high-dimensional data while preserving essential patterns and relationships between variables.

Syllabus

FoDA F22 Lecture 21

Taught by

UofU Data Science

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