What are the applications of matrix factorization in AI?
Matrix factorization is widely used in recommendation systems, natural language processing, and image processing.
Can you explain how it works in recommendation systems?
Sure! In recommendation systems, matrix factorization decomposes user-item interaction matrices to uncover latent factors.
What are some popular algorithms that use matrix factorization?
Popular algorithms include Singular Value Decomposition (SVD), Non-negative Matrix Factorization (NMF), and Alternating Least Squares (ALS).
Are there any limitations to using matrix factorization?
Yes, limitations include the need for a large amount of data and potential overfitting if not regularized properly.
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