Data Science, Mathematics, AI, Programming, Medium.
technique used to decompose a matrix into its constituent parts. It is widely used in data science for tasks such as matrix factorization, image processing, and recommendation systems. SVD involves finding the eigendecomposition of the covariance matrix of the data, which can be used to identify