Recently, graph neural networks (GNN) have become increasingly popular in various fields, including social networks, knowledge maps, recommendation systems, and even life sciences. GNN's ability to model the dependencies between nodes in a graph has made a breakthrough in the research field related to graph analysis. This article aims to introduce the basics of graph neural networks and two more advanced algorithms: DeepWalk and GraphSage.
