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.
Unsupervised Learning is a Machine Learning technique where models learn patterns and structures within data without labelled examples. By uncovering hidden relationships and clustering…