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Collaborative filtering models, a core technique in recommender systems, predict user preferences by analyzing interactions between users and items, identifying similar users or items, and recommending items liked by similar users or the user in question
C. Collaborative filtering is a foundational model for building a recommendation system as the input dataset is simple and the embeddings are learned for you. Matrix factorization is simply the model that applies to the collaborative filtering.
C) Collaborative filtering model