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Lecture
Recommender Systems: Matrix Factorization & Evaluation
Description
This lecture covers recommender systems, focusing on matrix factorization techniques for collaborative filtering. Topics include item-based collaborative filtering, latent factor derivation, matrix factorization optimization, weight aggregation matrices, and evaluation metrics like RMSE and NDCG.
Official source
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