A Python-based DS8001 course project that compares content-based, collaborative, popularity-based, hybrid, and SVD recommendation systems using real-world movie data from Kaggle, with a focus on empirical evaluation and performance analysis.
nltk recommendation-system tf-idf recommender-system cosine-similarity countvectorizer content-based-recommendation latent-factor-model svd-matrix-factorisation collobarative-filtering hybridrecommendation popularity-based-recommendation
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Updated
Apr 18, 2026 - TeX