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.

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📌 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.

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🚀 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

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📂 Project Structure