Introduction to Federated Learning

In-Depth Description

This resource introduces Federated Learning, a novel machine learning paradigm that allows for the training of AI models across multiple decentralized edge devices or servers holding local data samples, without exchanging the data itself. It highlights the benefits of this approach, particularly in terms of data privacy and security, and explores its applications in mobile devices, healthcare, and IoT. Ideal for researchers, data scientists, and engineers interested in privacy-preserving AI techniques.