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

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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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Digging into the Neo4j GDS library

The GDS library was first released in 2020. It was the successor of the Graph Algorithm plugin, which first appeared in 2019. Since then, a lot of improvements have been performed in terms of performance and standardization, and a lot of new features have been added, both in terms of algorithm parametrization and new kinds of algorithms. In the following subsections, we give an overview of its content and working principles.

GDS content

As the name suggests, the GDS library contains tools to be used in a data science project using data stored in Neo4j. This includes the following:

Path-related algorithms
Graph algorithms
Machine learning (ML) models and pipelines
Python client

Let’s talk in a bit more detail about each of these aspects, to understand when and where they are useful.

Path-related algorithms

In graph theory, traversing a graph to find specific paths from one node to another (typically the...

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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

Digging into the Neo4j GDS library

GDS content

Path-related algorithms

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Authors (2)