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Movie Recommendation System

🎬 Welcome to the Ultimate Movie Recommendation System! 🌟 Your go-to solution for discovering new and exciting movies tailored just for you. 🍿 Our system is powered by a vast dataset of 5000 movies, guaranteeing accurate and personalized recommendations to elevate your cinematic experience. Let the movie magic begin! 🎉✨

Features:

1. Comprehensive Movie Dataset 📊:

   • Our system is fueled by a vast dataset of 5000 movies, ensuring a diverse range of options to cater to every taste.

2. Accurate Recommendations 🎯:

   • Experience precision in movie suggestions, tailored specifically to your preferences for an immersive cinematic journey.

3. User-Friendly Interface 🖥️:

   • A seamless and intuitive interface designed for ease of use, making your movie exploration a delightful experience.

4. Personalized Movie Magic ✨:

   • Enjoy personalized recommendations that take into account your unique tastes, providing a curated selection just for you.

5. Exciting New Discoveries 🍿:

   • Uncover hidden gems and explore exciting new releases that align with your cinematic preferences.

6. Easy Integration 🚀:

   • Easily integrate our recommendation system into your movie-watching routine for instant access to fresh and exciting suggestions.

7. Open Source 🌐:

   • Our system is open source, allowing developers to contribute, customize, and enhance the movie recommendation experience.

8. Community Support 👥:

   • Join a vibrant community of movie enthusiasts to share recommendations, discuss favorite films, and stay updated on the latest cinematic trends.

Let the movie magic begin! 🎉✨

Architecture

How to Use

1. Clone the Repository:

   git clone https://github.com/kanugurajesh/Movie-Recommendation-System.git

2. Navigate to the Project Directory:

   cd Movie-Recommendation-System

3. Installing the frontend

   npm install

4. Installing the backend:

   python -m venv env
   env/bin/activate
   pip install -r requirements.txt

5. Setting up .env

   cp .env.example .env
   go to themoviedb and get an api key and add it in .env

6. Run the jupyter notebook

   mkdir helpers
   Run the notebook till the last cell and save the movies_list.pkl and similarity_movie.pkl in the helpers folder

7. Run the System[Backend]:

   activate the env[python environment]
   uvicorn server:app --reload

8. Run the System[Frontend]:

   npm run dev   

9. Input Your Favorite Movie: Select your favourite movie from the list of movies

10. Enjoy Your Recommendations: Sit back and let our system generate personalized movie recommendations just for you!

Demo

Contribution Guidelines

We welcome contributions to enhance and improve the Movie Recommendation System. If you have ideas or improvements, feel free to submit a pull request following our contribution guidelines.

Feedback and Issues

If you encounter any issues or have feedback, please open an issue on our GitHub repository. We appreciate your input and strive to make our system better with each update.

🔗 Links

Tech Stack

• Sveltekit
• Python
• fastapi
• Data preprocessing

Authors

• @kanugurajesh
• @rajesh604

Contributing

Contributions are always welcome!

See contributing.md for ways to get started.

Please adhere to this project's code of conduct.

Support

For support, you can buy me a coffee

License

Happy movie watching!