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Maybe you’ve heard about using graph data, or relationships, in machine learning pipelines for better accuracy or new types of predictions. But you’ve probably wondered: how exactly do I improve my predictive accuracy? The answer is graph embeddings: a technique to translate your graph into the right representation of your problem.
In this webinar, Dr. Alicia Frame will present on graph embeddings in Neo4j: a data encoding technique that allows you to make highly accurate predictions based on graph structure. Zach Blumenfeld will do a demo of graph embeddings from a consumer data set, showing you how to make accurate recommendations.
