LaughterLens is a collaborative filtering-based recommendation system that predicts user preferences for jokes using cosine similarity. It provides personalized joke recommendations, evaluates performance with Mean Absolute Error, and compares results with a baseline random recommender system.
python data-science machine-learning collaborative-filtering recommendation-system cosine-similarity ai-applications personalized-recommendations joke-recommendation user-based-filtering jester-dataset mae-evaluation
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Updated
Mar 24, 2025 - Jupyter Notebook