---
title: "Federated Learning"
description: "Federated Learning is a machine learning approach where model training occurs on decentralized devices, preserving data privacy and leveraging local computations."
date: "2024-05-23"
author:
  name: "Julian Rußmeyer"
  position: "UX/UI Designer"
  website: "https://www.linkedin.com/in/julian-russmeyer/"
related: 
  - text: "Tutorial: What is Federated Learning?"
    link: "/docs/framework/tutorial-series-what-is-federated-learning.html"
---

Federated learning is an approach to machine learning in which the model is trained on multiple decentralized devices or servers with local data samples without exchanging them. Instead of sending raw data to a central server, updates to the model are calculated locally and only the model parameters are aggregated centrally. In this way, user privacy is maintained and communication costs are reduced, while collaborative model training is enabled.
