Release Highlights: Neo4j Graph Data Science 2.3

02 Feb, 2023

Learn all about what’s new in Neo4j Graph Data Science 2.3! Join Zach Blumenfeld as he walks you through how to: Perform fast and scalable Graph ML using the Knowledge Graph Embedding – HashGNN Find the shortest, least expensive route to a location from multiple starting points using the Steiner Tree pathfinding algorithm Incorporate your negative examples to train link prediction models faster. Transform directed relationships into undirected relationships And more! Check out the resources below if you want to learn more —————– Resources —————– Notebooks / Demos / Technical Resources Steiner trees: – Docs: – Notebook Example: HashGNN: – Arxiv paper: – docs: – notebook example: Graph construct dataframe to graph example, improving ML with graph embeddings – Notebook example: Getting Started with Graph Data Science: – Sandbox: – Self-managed installation: – AuraDS: Graph Data Science 2.3 Links: Graph Data Science release announcement – What’s new summary – Graph Data Science – Docs: – GitHub: Python Client: – Docs: – GitHub:

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