Linear Algebra, Data Science, Applied Machine Learning.
np.linalg.eig(np.matmul(A, A.T)) eigenvalues_R, eigenvectors_R = np.linalg.eig(np.matmul(A.T, A)) Now, compare it against the ‘all-in-one’ step using np.linalg.svd below and you will notice that we end up with the same results, with the caveat that some columns may differ by a factor of -1, and/or