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user-personalization

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Md-Emon-Hasan / BookSage-AI

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Full-stack hybrid book recommendation system combining Collaborative Filtering and Content-Based Filtering with weighted hybrid scoring, modular data pipelines, and model persistence. Deployed via Flask with responsive HTML/CSS UI and integrated CI/CD for production-ready, scalable, and interactive recommendations.

data-science machine-learning collaborative-filtering recommendation-system python-project hybrid-recommendation hybrid-recommender-system ai-project hybrid-recommendation-engine content-based-filtering personalized-recommendation book-recommendation-model book-recommendation-system cold-start-problem collaborative-filtering-recommendation dockerized-app ai-recommendation-system user-personalization ai-recommendations personalized-recommendation-system
  • Updated Sep 24, 2025
  • Jupyter Notebook

kantkrishan0206-crypto / -CineMatch

Star 0

Movie Recommender AI System: "An intelligent Movie Recommender System that suggests films using content-based, collaborative, and hybrid filtering. Built with Python and ML algorithms, it delivers personalized recommendations with data insights and a simple web interface."

python docker data-science numpy scikit-learn pandas collaborative-filtering dataset recommendation-system movie-ratings hybrid-recommender-system joblib content-based-filtering fastapi surprise-library ml-models streamlit-application open-source-ai user-personalization movie-recommender-model-training
  • Updated Oct 5, 2025
  • Jupyter Notebook

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