The Movie Recommendation System is designed to provide personalized movie suggestions based on user preferences, ratings, and genres. It utilizes modern recommendation algorithms and a user-friendly interface for an enhanced movie discovery experience.
- Personalized movie recommendations
- User authentication and profile management
- Movie rating and review system
- Search and filter functionality
- Responsive UI/UX design
- HTML, CSS, JavaScript – For the user interface
- React.js (Optional) – If using a modern frontend framework
- Node.js + Express.js OR Python + Flask/Django – For API development
- MongoDB / PostgreSQL / MySQL – For data storage
- TMDb API / Custom Movie Dataset – For movie data
- Machine Learning (Scikit-learn, TensorFlow, or PyTorch) – For recommendation algorithms (if applicable)
/movie_recommendation
/src # Source Code (Frontend & Backend)
/docs # Documentation (Requirements, Design, API Docs)
/tests # Test Cases & Scripts
/designs # UI/UX Wireframes from Figma
- Install Node.js & npm (if using Node.js)
- Install Python 3 & pip (if using Python)
- Install MongoDB/PostgreSQL/MySQL (if using a database)
git clone https://github.com/yourusername/movie_recommendation.git
cd movie_recommendationIf using Node.js:
cd src
npm installIf using Python:
cd src
pip install -r requirements.txtFor Node.js:
npm startFor Python (Flask/Django):
python app.py # Flask
python manage.py runserver # DjangoGo to http://localhost:3000/ (or the appropriate port) to access the application.
- Fork the repository
- Create a feature branch (
git checkout -b feature-branch) - Commit your changes (
git commit -m "Added new feature") - Push to the branch (
git push origin feature-branch) - Open a Pull Request
This project is licensed under the MIT License.