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