Python, R Programming, R, Linear Algebra, Calculus.
decomposes a matrix into three matrices: U, S, and V. SVD has many applications in data science, such as dimensionality reduction and recommender systems. Here's an example of how to perform SVD using Python: pythonCopy code import numpy as np X = np.array([[1, 2, 3], [4, 5, 6], [7, 8, 9]]) U, S, V