PROD MovieLens
DIR Python
SCENE Hybrid Rec
TAKE 2

Movie Recommendation System

Content-Based • Collaborative Filtering • Hybrid

↓

How It Works

🎬

Content-Based

Builds a user taste profile from genre preferences using TF-IDF weighting. Recommends movies with similar genre vectors to what you've enjoyed before.

Genre Matching
👥

Collaborative

Finds movies that frequently co-occur with your rated films across all users. Leverages collective viewing patterns to surface hidden picks.

Co-occurrence
⚖

Hybrid

Multiplies content-based and collaborative scores to combine both signals. Surfaces movies that match your taste AND are popular among similar viewers.

Combined Score

Try It Out

Step 1

Enter a User ID

Pick a user from the MovieLens dataset (1–671)

Architecture

📦
Input
MovieLens 100K
➜
⚙
Processing
Python + pandas
➜
🎬
Content
TF-IDF Genres
➜
👥
Collaborative
Co-occurrence
➜
⚖
Hybrid
Score Fusion
Python 3 pandas numpy MovieLens