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Clustering deep dive with the Neo4j graph database

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Nathan S.
Clustering deep dive with the Neo4j graph database

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Data scientists use clustering algorithms like k-means and HDBSCAN to discover groups of related items. Graph databases provide tools to analyze relationships. Walking through a clustering algorithm with graph database tools sheds new light on unsupervised machine learning.

In this session we'll do a deep dive into the density-based clustering algorithm HDBSCAN. You'll come away with a better understanding of how HDBSCAN works and see hands-on examples with Neo4j's Cypher query language, Graph Data Science library, APOC library, and Bloom data visualization tool.
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