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

Importing existing data into a brand-new database is always a concern, as we covered in this chapter. From a flat (a non-graph format) file, you can identify node labels and relationship types between them, transforming a flat dataset into a real graph. Whether your data is stored as CSV, JSON, on your local disk or distant server, or via an API endpoint, you can now load this data into Neo4j and start exploring your graph. You also learned about the Neo4 Data Importer tool, which is used to import data stored as CSV files in a cloud-hosted Neo4j database (Aura).

You also learned about public knowledge graphs, such as Wikidata, which can be used to extend your knowledge by importing more data about a specific topic.

Finally, you learned how to import your data into the cloud thanks to the Neo4j Data Importer application.

Being able to create a graph dataset is only the beginning, though. Like any dataset, graph datasets are very different from one to another. While...

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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)