The Neo4j Graph Data Science Library Manual v2.19

The manual covers the following areas:

Introduction — An introduction to the Neo4j Graph Data Science library.
Installation — Instructions for how to install and use the Neo4j Graph Data Science library.
Common usage — General usage patterns and recommendations for getting the most out of the Neo4j Graph Data Science library.
Graph management — A detailed guide to the graph catalog and utility procedures included in the Neo4j Graph Data Science library.
Graph algorithms — A detailed guide to each algorithm in their respective categories, including use-cases and examples.
Machine learning — A detailed guide to the machine learning procedures included in the Neo4j Graph Data Science library.
Production deployment — This chapter explains advanced details with regards to common Neo4j components.
Python client — Documentation of the Graph Data Science client for Python users.
Operations reference — Reference of all procedures contained in the Neo4j Graph Data Science library.
Migration from Graph Data Science library Version 1.x — Additional resources - migration guide, books, etc - to help using the Neo4j Graph Data Science library.
Migration from Legacy to new Cypher projections — Migration guide to help migration from the Legacy Cypher projections to the new Cypher projections.

The source code of the library is available at GitHub. If you have suggestions for improving the library or want to report a problem, you can create a new issue.