Machine Learning, Artificial Intelligence, Mathematics.
foundation to untangle data into independent components. PCA skips less significant components. Obviously, we can use SVD to find PCA by truncating the less important basis vectors in the original SVD matrix. Matrix diagonalization In the article on eigenvalue and eigenvectors, we describe a method