Recommender Systems: Matrix Factorization & Evaluation

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.