Until now, few companies outside of Google and Facebook have had the AI foresight and resources to leverage graph embeddings. This powerful and innovative technique calculates the shape of the surrounding network for each piece of data inside of a graph, enabling far better machine learning predictions. Neo4j for Graph Data Science version 1.4 democratizes these innovations to upend the way enterprises make predictions in diverse scenarios from fraud detection to tracking customer or patient journey, to drug discovery and knowledge graph completion. Caption: Graph embeddings are a powerful tool to abstract the complex structures of graphs and reduce their dimensionality. This technique opens up a wide range of uses for graph-based machine learning.
Oct-26-2020, 08:55:42 GMT