Introduction to Graph Neural Networks with NVIDIA cuGraph-DGL

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Graph neural networks (GNNs) have emerged as a powerful tool for a variety of machine learning tasks on graph-structured data. These tasks range from node classification and link prediction to graph classification. They also cover a wide range of applications such as social network analysis, drug discovery in healthcare, fraud detection in financial services, and…

Working on speeding up GNNs at scale? Got questions or feature requests? Hit us up on our GitHub: rapidsai/cugraph.