Data Science, Machine Learning, Dimensionality Reduction, Python.
covariance matrix of the data. Compute the eigenvectors of this matrix. We use Eigenvectors corresponding to the largest eigenvalues. That is to reconstruct a large fraction of variance of the original data. Hence, we are left with a lesser number of eigenvectors. And there might have been some