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Principal Component Analysis: Everything You Need To Know
Covariance, eigenvalues, variance and everythingImage by Author
Principal Component Analysis ( PCA ) is a popular technique to reduce the dimensions of the data and is included in most ML/DS courses under the section ‘unsupervised learning’. There are a number of blogs that explain PCA alongside YT videos, so why is this blog here?
Another blog on PCA?
As an ML learner who loves Math more, I found every blog on PCA incomplete. Summarizing each blog I …