Data Science, Linear Algebra, Dimensionality Reduction, Math.
data matrix! (You just need to multiply the matrix “V” from the right side on X_c = UΣV’ ) Summary PCA projects the data onto the principal components where the variance of the data is maximized (or the total distances from each point to the axis is minimized) You can derive why PCA is all about