ai-tutor-skill

# Explanation of Federated Learning

Federated learning is like a group of students collaborating on a project without sharing their individual notes. Each student (or device in this case) trains a model on their local data and only shares the updated model parameters with a central server. This way, sensitive data never leaves the device, ensuring privacy.

**Real-world example:**

A healthcare company like **HospitalChain** in the **healthcare industry** could use federated learning to improve disease prediction models. Each hospital would train the model on its local patient data, and the central server would aggregate the updates. This way, HospitalChain could build a robust model without compromising patient privacy.