This project demonstrates the implementation of federated learning in a web-based environment. It features a full-stack application with a React frontend and FastAPI backend, showcasing how machine learning models can be trained across distributed data sources while preserving data privacy. The system includes a public API endpoint for model training and inference, with the entire solution containerized using Docker for easy deployment and scaling.