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Dimensionality Reduction (PCA, SVD)

Dimensionality reduction is basically a technique to convert our data to a lower dimensional form where we have non correlated variables that hopefully explain most of the variance in our data. Principle Component Analysis (PCA) and Singular Value Decomposition (SVD) are just 2 methods of dimensionality reduction. Associated Roam Page