Movie Recommender System

This is a content-based movie recommender system built using Python, Streamlit, and scikit-learn. It suggests similar movies based on the one you select, using cosine similarity on movie metadata features.

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🚀 Features

• Recommend top 5 movies similar to a selected movie
• Movie posters fetched via TMDb API
• Clean and interactive UI with Streamlit
• Lightweight and easy to deploy.

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📦 Tech Stack

• Python 3.8+

• Streamlit

• Pandas

• numpy

• Scikit-learn

• Requests

• Pickle (for precomputed similarity & movie data)

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Dataset

The Movie Database (TMDb) in accordance with their terms of use.

Download the (Dataset)[https://www.kaggle.com/datasets/tmdb/tmdb-movie-metadata]

🖥️ Live Demo

Coming soon on Streamlit Cloud or Render!

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🔧 Setup Instructions

1. Clone the Repository

git clone https://github.com/your-username/movie-recommender.git
cd movie-recommender

2. Create a Virtual Environment (optional)

python -m venv venv
source venv/bin/activate  # On Windows: venv\Scripts\activate

3. Install Dependencies

pip install -r requirements.txt

4. Add Your TMDb API Key

Create a file called .env (or update directly in the code):

TMDB_API_KEY=your_api_key_here

Or edit this line in app.py:

url = f"https://api.themoviedb.org/3/movie/{movie_id}?api_key=YOUR_KEY&language=en-US"

5. Run the App

streamlit run app.py

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📁 Folder Structure

├── app.py                      # Main Streamlit app
├── Model/
│   ├── movie_list.pkl          # Movie metadata
│   ├── similarity.pkl          # Precomputed similarity matrix
├── requirements.txt
└── README.md

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📌 How It Works

1. Load movie metadata and similarity matrix
2. Select a movie from the dropdown
3. Recommend top 5 similar movies based on cosine similarity
4. Fetch and display posters via TMDb API

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💡 Future Improvements

• Include genre and rating filters
• Add collaborative filtering model
• Deploy on Streamlit Cloud or Render
• Integreate AI to explain each movie and how it relates

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🤝 Contributing

Feel free to fork this repo, open issues, or submit pull requests.