# Startup Validator This project is an end-to-end ML-powered startup validator that analyzes business ideas and predicts their success probability. ## Features - Data Pipeline to scrape and process data from various sources. - Machine Learning Model to analyze business ideas using NLP and ensemble methods. - Validation Framework to score ideas and provide feedback. - Full-Stack Web Application with React frontend and FastAPI backend. - MLOps Best Practices for model versioning, containerization, and CI/CD. ## Setup Guide ### Prerequisites - Python 3.9+ - Node.js - Docker - GitHub account ### Steps 1. Clone the repository: ```bash git clone https://github.com/yourusername/startup-validator.git cd startup-validator ``` 2. Set up environment variables: - Create a `.env` file with the following content: ``` CRUNCHBASE_API_KEY=your_crunchbase_api_key NEWS_API_KEY=your_news_api_key ``` 3. Install dependencies: ```bash pip install -r requirements.txt ``` 4. Run the data pipeline: ```bash python data_pipeline.py ``` 5. Train the machine learning model: ```bash python ml_model.py ``` 6. Start the backend server: ```bash uvicorn backend.main:app --reload ``` 7. Start the frontend application: ```bash cd frontend npm install npm start ``` 8. Open your browser and navigate to `http://localhost:3000` to use the application. 9. To build and run the Docker container: ```bash docker build -t startup-validator . docker run -p 8000:8000 startup-validator ``` 10. Set up CI/CD pipeline: - Push the code to GitHub and configure GitHub Actions with your Docker Hub credentials.# startup-validator