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user-personalization

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Hybrid book recommendation system fusing a scikit-learn k-nearest-neighbors collaborative filtering model with a TF-IDF cosine-similarity content model, weighted-average combined and trained on the 1.1 million rating Book-Crossing dataset, served through a FastAPI backend with TTL caching, a decoupled React frontend, and Docker Compose deployment.

  • Updated Aug 5, 2026
  • Python

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