Data Science, Linear Algebra, Dimensionality Reduction, Math.
we computed eigenvectors and eigenvalues, eigendecomposition based PCA needs to calculate the covariance matrix first. The covariance matrix was “f” by “f”. If “f” is small, it won’t be a problem. But imagine a huge “f”, let’s say you are dealing with an image. “f” suddenly becomes a huge number,