Matrix Factorization
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May 1, 2024
Updated May 11, 2025
21 minute read
Matrix factorization is a powerful mathematical technique widely used in data science and machine learning. At its core, it involves breaking down a large matrix into the product of two or more smaller, simpler matrices. Think of it like factoring a number; for instance, 48 can be factored into 4 x 12 or 6 x 8. Matrices, being more complex, allow for various types of factorization. The primary goal is often to uncover underlying, or latent, structures within the data. This process can reveal hidden patterns and relationships that are not immediately obvious from the original data.
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