You're reading from Graph Data Science with Neo4j Learn how to use Neo4j 5 with Graph Data Science library 2.0 and its Python driver for your project

Product type Paperback

Published in Jan 2023

Publisher Packt

ISBN-13 9781804612743

Length 288 pages

Edition 1st Edition

Languages

Python

Tools

Neo4j

Concepts

Data Science

Author (1):

Estelle Scifo

View More author details

Table of Contents (16) Chapters

Preface

1. Part 1 – Creating Graph Data in Neo4j

2. Chapter 1: Introducing and Installing Neo4j FREE CHAPTER

3. Chapter 2: Importing Data into Neo4j to Build a Knowledge Graph

4. Part 2 – Exploring and Characterizing Graph Data with Neo4j

5. Chapter 3: Characterizing a Graph Dataset

6. Chapter 4: Using Graph Algorithms to Characterize a Graph Dataset

7. Chapter 5: Visualizing Graph Data

8. Part 3 – Making Predictions on a Graph

9. Chapter 6: Building a Machine Learning Model with Graph Features

10. Chapter 7: Automatically Extracting Features with Graph Embeddings for Machine Learning

11. Chapter 8: Building a GDS Pipeline for Node Classification Model Training

12. Chapter 9: Predicting Future Edges

13. Chapter 10: Writing Your Custom Graph Algorithms with the Pregel API in Java

14. Index

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Introducing the GDS Python client

The previous chapters introduced the Neo4j GDS library. There, you discovered the concepts of projected graphs and the procedures to run specific graph algorithms from Cypher. If you do not have direct access to Neo4j Browser, or if you want to automate your data processing, it might be convenient to be able to use GDS procedures from Python. One possible approach is to use the Neo4j Python driver introduced in a preceding chapter (Chapter 3, Characterizing a Graph Dataset) and write code like this:

# driver instantiation
from neo4j import GraphDatabase
driver = GraphDatabase.driver(
      "bolt://localhost:7687",
      auth=("neo4j", "<PASSWORD>")
)
with driver.session() as s:
     # create projected graph named 'pG'
     s.run("CALL gds.graph.project('pG', 'NodeB',...

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You're reading from Graph Data Science with Neo4j Learn how to use Neo4j 5 with Graph Data Science library 2.0 and its Python driver for your project

Table of Contents (16) Chapters

Introducing the GDS Python client

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Authors (2)