A terminal-first personalized movie recommendation engine powered by hybrid retrieval (BM25 + HNSW), cross-encoders, and learning-to-rank on MovieLens-25M.
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Updated
Aug 13, 2026 - Python
A terminal-first personalized movie recommendation engine powered by hybrid retrieval (BM25 + HNSW), cross-encoders, and learning-to-rank on MovieLens-25M.
UCI EECS 298 NS: Graph Recommendation System (course project)
Mini recommendation engine using MovieLens-100k and SVD. Demonstrates skills in collaborative, filtering, model training and deployment
Graph Neural Network recommendation system using LightGCN on MovieLens 100K with a FastAPI serving layer and interactive frontend
Movie recommendation engine using SVD Matrix Factorization and Collaborative Filtering on MovieLens data with a Flask web app.
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