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What is the purpose of Singular Value Decomposition (SVD) in Recommendation Systems? Answer choices Select only one option To decompose the user-item matrix into latent
What is the purpose of Singular Value Decomposition (SVD) in Recommendation Systems? Answer choices Select only one option To decompose the user-item matrix into latent factors To identify the most or least popular items in the dataset To increase the number of features/dimensions in the user-item matrix To replace missing values in the user-item matrix with an irrational number
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