Svd, Machine Learning, Data Science, Artificial Intelligence, Matrix Factorization.
SVD is capable of handling any type of matrix, including rectangular matrices, and it is a useful tool for dimensionality reduction, image processing, and data analysis. Principal Component Analysis (PCA): PCA is a dimensionality reduction technique that uses SVD to find the directions in the data