Svd.
2.01213698e+00]] In the above example, we first load the tabular dataset into a NumPy array. Then, we perform SVD using np.linalg.svd() function, which decomposes the dataset into singular values, left singular vectors (U), and right singular vectors (V^T). We then select the top k singular values