A smart restaurant discovery platform for European cities
An intelligent restaurant recommendation system that helps users discover their perfect dining experience in London, Paris, and Rome. Using machine learning algorithms and user preference analysis, it provides personalized restaurant suggestions tailored to individual tastes, dietary requirements, and dining priorities.
- Smart Recommendations: AI-powered matching based on user preferences
- Multi-City Support: London, Paris, and Rome restaurant databases
- Personalized Experience: Learns from user feedback and selections
- Rich Restaurant Data: Photos, ratings, reviews, and detailed information
- Intuitive Interface: Modern, responsive web application
res-rec-system/
├── frontend/ # React TypeScript application
├── backend/ # Flask Python API
├── LICENSE # MIT License
├── .gitignore # Git ignore rules
└── README.md # This file
-
Clone the repository
git clone https://github.com/yourusername/res-rec-system.git cd res-rec-system -
Set up environment variables
cp env.example .env # Edit .env with your configuration -
Start the backend
cd backend python -m venv venv source venv/bin/activate # Windows: venv\Scripts\activate pip install -r requirements.txt flask run
-
Start the frontend
cd frontend npm install npm run dev -
Open your browser to
http://localhost:5173
For detailed documentation, setup instructions, and technical details, see:
- Frontend Documentation - Complete project documentation
- Backend API Documentation - API endpoints and backend architecture
- React 18 with TypeScript
- TailwindCSS for styling
- Vite for build tooling
- Custom hooks for API integration
- Flask Python web framework
- MongoDB for data persistence
- scikit-learn for ML algorithms
- NumPy/Pandas for data processing
- Production-Ready: Comprehensive error handling and user feedback
- Scalable Architecture: Clean separation of concerns and modular design
- AI Integration: Real machine learning for personalized recommendations
- Modern Stack: Latest versions of React, TypeScript, and Python frameworks
- User-Centered: Intuitive interface with accessibility considerations
We welcome contributions! Please see our Contributing Guidelines for details.
This project is licensed under the MIT License - see the LICENSE file for details.
Built with ❤️ for food lovers everywhere