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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