A Comprehensive Introduction to Graph Neural Networks (GNNs) | DataCamp

A Graph is the type of data structure that contains nodes and edges. A node can be a person, place, or thing, and the edges define the relationship between nodes. The edges can be directed and undirected based on directional dependencies. In the example below, the blue circles are nodes, and the arrows are edges. The direction of edges defines dependencies between two nodes. Image by Author Let’s learn about the complex Graph dataset: Jazz Musicians Network. It contains 198 nodes and 2742 edges. In the community graph plot below, different colors of nodes represent various communities of Jazz musicians and the edges connecting them. There is a web of collaboration where a single musician has relationships within and outside the community.  Community Graph Plot by Jazz Musicians Network Graphs are excellent in dealing with complex problems with relationships and interactions. They are used in pattern recognition, social networks analysis, recommendation systems, and semantic analysis. C

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• Kenson Hui