pavanbadempet/Movie-Recommendation-System
Content-based movie recommendation engine using SBERT semantic embeddings, FAISS vector search, and FastAPI. Features 33k+ movies with real-time TMDB enrichment.
This system helps streaming platforms, e-commerce sites, or digital content libraries offer highly relevant recommendations. It takes user queries like 'documentaries about minimalists' or 'warm winter coat for skiing' and provides tailored results, even if keywords aren't an exact match. Content curators and product managers would use this to improve content discoverability and user engagement.
Use this if you need to offer context-aware content recommendations or product suggestions based on the true meaning of a user's query, rather than just exact keyword matches.
Not ideal if your recommendation needs are met by simple, exact keyword searches or if you primarily rely on collaborative filtering based on user behavior.
Stars
8
Forks
—
Language
Python
License
MIT
Category
Last pushed
Mar 01, 2026
Commits (30d)
0
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