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FoDA F22 Lecture 20
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Save Big on Coursera Plus. 7,000+ courses at $160 off. Limited Time Only! Grab it Learn advanced dimensionality reduction techniques in this university lecture covering rank-k approximation methods, their connection to eigendecomposition, and the power method algorithm for finding dominant eigenvalues and eigenvectors in large matrices.

Dimensionality Reduction: Rank-k Approximation and Eigen-decomposition - Lecture 20

UofU Data Science
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