Eigenvectors, Eigenvalue, Data Science, Machine Learning, Principal Component.
is then this: SVD decomposes a matrix A into U (left singular vectors), big sigma (diagonal vector of singular values) and V (right singular vectors) (source) The final piece of the puzzle is, how do we actually find these singular vectors/values? And what exactly are they? Well, like we figured