Graph Neural Networks are machine learning models designed to handle data structured as graphs. They can capture relationships and dependencies between entities and perform tasks such as node classification, link prediction, and graph generation. Graph Neural Networks are valuable for analysing social networks, biological networks, and recommendation systems.
Federated Learning is a privacy-preserving technique where AI models are trained across multiple decentralised devices or systems without sharing raw data. Instead, only aggregated…