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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Part 2 – Exploring and Characterizing Graph Data with Neo4j

In this part, you will learn how to characterize a graph dataset: which information and metrics can be provided to distinguish one dataset from another. You will be introduced to the Neo4j Graph Data Science (GDS) library and the most common graph algorithms to analyze the graph topology, finding important nodes or clusters of highly connected nodes. You will also discover some tools to visually explore graph data.

This part includes the following chapters:

Chapter 3, Characterizing a Graph Dataset
Chapter 4, Using Graph Algorithms to Characterize a Graph Dataset
Chapter 5, Visualizing Graph Data

The rest of the chapter is locked

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

Part 2 – Exploring and Characterizing Graph Data with Neo4j

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Authors (2)