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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Exercise

In order to get more proficient with the GDS Python client, I recommend you redo the analysis from Chapter 4, Using Graph Algorithms to Characterize a Graph Dataset, with it. That is, do the following:

Build projected graphs that contain the following:
1. Person nodes and all relationships.
2. Person and Movie nodes with all relationships.
3. Person nodes with KNOWS relationships, undirected.
4. Person nodes with KNOWS relationships aggregated to keep one single relationship between the same two nodes.
5. Person nodes with KNOWS relationships aggregated to store the number of relationships between the same two nodes in a weight property.
6. Using Cypher projection: Movie nodes and a relationship between two movies when at least one person acted in or directed both movies. Save the movie’s release year and the relationship’s weight (the number of persons collaborating on both movies) as node and relationship properties, respectively.
Run graph algorithms: Using the projected...

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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

Exercise

Unlock this book and the full library FREE for 7 days

Authors (2)