Book Image

Graph Data Science with Neo4j

By : Estelle Scifo
5 (1)
Book Image

Graph Data Science with Neo4j

5 (1)
By: Estelle Scifo

Overview of this book

Neo4j, along with its Graph Data Science (GDS) library, is a complete solution to store, query, and analyze graph data. As graph databases are getting more popular among developers, data scientists are likely to face such databases in their career, making it an indispensable skill to work with graph algorithms for extracting context information and improving the overall model prediction performance. Data scientists working with Python will be able to put their knowledge to work with this practical guide to Neo4j and the GDS library that offers step-by-step explanations of essential concepts and practical instructions for implementing data science techniques on graph data using the latest Neo4j version 5 and its associated libraries. You’ll start by querying Neo4j with Cypher and learn how to characterize graph datasets. As you get the hang of running graph algorithms on graph data stored into Neo4j, you’ll understand the new and advanced capabilities of the GDS library that enable you to make predictions and write data science pipelines. Using the newly released GDSL Python driver, you’ll be able to integrate graph algorithms into your ML pipeline. By the end of this book, you’ll be able to take advantage of the relationships in your dataset to improve your current model and make other types of elaborate predictions.
Table of Contents (16 chapters)
1
Part 1 – Creating Graph Data in Neo4j
4
Part 2 – Exploring and Characterizing Graph Data with Neo4j
8
Part 3 – Making Predictions on a Graph

Preface

Data science today is a core component of many companies and organizations taking advantage of its predictive power to improve their products or better understand their customers. It is an ever-evolving field, still undergoing intense research. One of the most trending research areas is graph data science (GDS), or how representing data as a connected network can improve models.

Among the different tools on the market to work with graphs, Neo4j, a graph database, is popular among developers for its ability to build simple and evolving data models and query data easily with Cypher. For a few years now, it has also stood out as a leader in graph analytics, especially since the release of the first version of its GDS library, allowing you to run graph algorithms from data stored in Neo4j, even at a large scale.

This book is designed to guide you through the field of GDS, always using Neo4j and its GDS library as the main tool. By the end of this book, you will be able to run your own GDS model on a graph dataset you created. By the end of the book, you will even be able to pass the Neo4j Data Science certification to prove your new skills to the world.