Data Science, Machine Learning, Svd, Data Reduction, Mathematics.
SVD It is the reduced version of full SVD. Truncated SVD It is the next version of economy SVD where we choose only K features. 3. Applications There are many applications of SVD. Some of them are as follows: Estimation of pseudo-inverse of non-square matrices (Ax=b) Low-Rank Matrix Approximation