Graph-based ML is a powerful tool that utilizes the connections between entities in the graph to provide more accurate predictions. Amazon Neptune ML uses graph neural networks (GNNs), powered by the Deep Graph Library (DGL), to make easy, fast, and more accurate ML predictions. Since launching in 2020, Neptune ML has been used for graph applications such as recommendation engines, knowledge graphs, entity/identity resolution, consumer 360, and fraud detection. In this session, learn how you can apply Neptune ML to solve for common use cases while reducing the time, complexity, and cost of maintaining systems through Neptune ML's automation of the model-building lifecycle.
