Machine learning · Recommendation systems
Movie Recommendations.
Find similar films with content-based recommendations.
01 / Overview
What it does.
This project lets users choose a film and find other titles with similar content. I used Python and scikit-learn for the recommendation logic, with a searchable catalogue and TMDB posters to make the results easy to browse.
02 / Implementation
How it works.
- 01Select a film
- 02Compare movie features
- 03Rank similar titles
- 04Display recommendations
Content-based similarity
The system compares movie features and ranks related titles. Recommendations are based on the selected film’s content rather than a user’s viewing history.
From model output to an application
FastAPI provides the API layer for the recommendation logic, while Next.js provides the web interface. Users select a film and browse the suggested titles with posters supplied by TMDB.
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