For PCA it doesn't help to overthink the deep mathematics of eigenvalues and eigenvectors. You can think of eigenvalues and eigenvectors as a kind of factorization of a matrix that captures all the ...

Principal component analysis (PCA) is a classical machine learning technique. The goal of PCA is to transform a dataset into one with fewer columns. This is called dimensionality reduction. The ...