Item Profiling: TF-IDF, BM25, n-grams, and Categorical Feature Encoding — Math + NumPy

Foundation of content-based recommenders: converting item to numerical vector. Full TF-IDF formula derivation + from-scratch NumPy implementation, BM25 vs TF-IDF difference, n-grams on movie titles, categorical encoding (one-hot, target, frequency).