Data Science, Linear Algebra, Dimensionality Reduction, Math.
more than a million in some cases. Then computing the covariance becomes infeasible. This is where SVD based PCA can help. Let’s see why. If you remember the SVD we covered last time, the centered data can be decomposed into three different matrices. “U” and “V” are unitary matrices and “Σ” is a