Mathematics, Linear Algebra, Machine Learning, Data Science.
5, 6], [7, 8, 9]]) # Perform SVD U, S, VT = np.linalg.svd(A) print("U:\n", U) print("S:\n", S) print("VT:\n", VT) Why It’s useful : SVD can be utilized for dimensionality reduction by retaining only the most significant singular values and their corresponding singular vectors. This is particularly