Svd, Machine Learning, Data Science, Artificial Intelligence, Matrix Factorization.
robust technique that is not affected by outliers and is able to preserve the important information in the data. This makes it useful in fields such as image processing and data analysis, where outliers and noise are common. Low-Rank Approximations: SVD can be used to find low-rank approximations