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Recommendation Engine

A hybrid recommendation engine that combines Content-Based Filtering and Collaborative Filtering to provide personalized movie recommendations.
Built using Python, Scikit-learn, Pandas, and Streamlit.

📌 Project Overview

This system recommends movies to users based on:

  1. Content Similarity (tags + descriptions)
  2. User Similarity (ratings by similar users)
  3. Hybrid Model (combined top recommendations)

The project loads a dataset, preprocesses it, builds models, computes similarity matrices, and exposes a clean Streamlit UI for real-time recommendations.

🚀 Features

  • Content-Based Model
  • Collaborative Filtering Model
  • Hybrid Recommendation System
  • Trending Movies Display
  • Interactive UI using Streamlit
  • Modular project structure
  • Fully documented, easy to extend

📂 Project Structure