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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Summary

In this chapter, we’ve explored a few helpful tools for graph data visualization. First, networkx has helped us visualize relatively small graphs in a Jupyter notebook. We have explored the challenge of graph data visualization and learned about graph layout. In the second part, we have used another great tool—part of the Neo4j ecosystem—called Neo4j Bloom. It has many features allowing to deal with graph data stored in Neo4j without writing any Cypher query. We have focused on how to customize the appearance of the graph, choosing the node’s color and size.

Finally, we have discovered a very powerful tool we have to know about when dealing with GDS: Gephi. Here, again, we have focused on node appearance configuration.

In all cases, you are highly encouraged to dig deeper into these tools by yourself, using your own data and/or exploring the features we can’t talk about in this book (unless we double its length, but then nobody would...

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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

Summary

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Authors (2)