Graph Data Science with Neo4j (Packt)
Monday, 06 March 2023

This practical guide to Neo4j and the GDS library offers step-by-step explanations of essential concepts and practical instructions for implementing data science techniques on graph data using Neo4j version 5 and its associated libraries. Estelle Scifo starts by showing how to query Neo4j with Cypher and how to characterize graph datasets before moving on to the new and advanced capabilities of the GDS library that enable you to make predictions and write data science pipelines.


Scifo shows how to use the newly released GDSL Python driver to integrate graph algorithms into ML pipelines and by the end of the book show how to take advantage of the relationships in datasets to improve models and make other types of elaborate predictions.

Author: Estelle Scifo
Publisher: Packt
Date: January 2023
Pages: 288
ISBN: 978-1804612743
Print: 180461274X
Kindle: B0BT1TQHPC
Audience: Python developers interested in Neo4j
Level: Intermediate
Category: Data Science


Topics covered:


  • Use the Cypher query language to query graph databases such as Neo4j
  • Build graph datasets from your own data and public knowledge graphs
  • Make graph-specific predictions such as link prediction
  • Explore the latest version of Neo4j to build a graph data science pipeline
  • Run a scikit-learn prediction algorithm with graph data
  • Train a predictive embedding algorithm in GDS and manage the model store


For recommendations of data mining books see Reading Your Way Into Big Data in our Programmer's Bookshelf section.

For recommendations of Python books see Books for Pythonistas and Python Books For Beginners in our Programmer's Bookshelf section.

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