Movie Recommender
Content-Based & Collaborative Filtering Machine Learning Engine
Technical Blueprint
ArchitectureAI & ML
Release Year2025
Deployment StatusComplete
Core Technologies3 Libraries / Tools
Technologies Deployed
Project Architecture & Overview
Machine learning recommendation platform analyzing 5,000+ movies from the TMDB dataset. Vectorizes genre, cast, director, and plot synopsis tokens into a high-dimensional feature matrix and computes cosine similarity angles to generate highly relevant movie suggestions.
Key Engineering Milestones
- ✦TF-IDF text vectorization and Cosine Similarity metric computing match scores
- ✦Dynamic TMDB API integration fetching high-resolution movie posters and trailers
- ✦Interactive Streamlit UI delivering 5 personalized recommendations in <100ms
- ✦Hybrid recommendation logic blending genre tags and director filmography
