Primitive Movie Recommender

A content-based recommendation engine built with Python and Scipy using the MovieLens 32M dataset. It explores the transition from item-item to user-item recommendations, evaluates implicit vs. explicit feedback models, and demonstrates how popularity filtering boosts recommendation precision from under 1% to over 16%.

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