Hands-On Graph Analytics with Neo4j

By Estelle Scifo
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  1. Section 1: Graph Modeling with Neo4j

About this book

Neo4j is a graph database that includes plugins to run complex graph algorithms.

The book starts with an introduction to the basics of graph analytics, the Cypher query language, and graph architecture components, and helps you to understand why enterprises have started to adopt graph analytics within their organizations. You’ll find out how to implement Neo4j algorithms and techniques and explore various graph analytics methods to reveal complex relationships in your data. You’ll be able to implement graph analytics catering to different domains such as fraud detection, graph-based search, recommendation systems, social networking, and data management. You’ll also learn how to store data in graph databases and extract valuable insights from it. As you become well-versed with the techniques, you’ll discover graph machine learning in order to address simple to complex challenges using Neo4j. You will also understand how to use graph data in a machine learning model in order to make predictions based on your data. Finally, you’ll get to grips with structuring a web application for production using Neo4j.

By the end of this book, you’ll not only be able to harness the power of graphs to handle a broad range of problem areas, but you’ll also have learned how to use Neo4j efficiently to identify complex relationships in your data.

Publication date:
August 2020
Publisher
Packt
Pages
510
ISBN
9781839212611

 
Section 1: Graph Modeling with Neo4j

This part will review the basics of Neo4j and Cypher needed for this book. We will then explore a classic application of graph modeling: recommendation engines.

This section consists of the following chapters:

About the Author

  • Estelle Scifo

    Estelle Scifo possesses over 7 years’ experience as a data scientist, after receiving her PhD from the Laboratoire de l’Accélérateur Linéaire, Orsay (affiliated to CERN in Geneva). As a Neo4j certified professional, she uses graph databases on a daily basis and takes full advantage of its features to build efficient machine learning models out of this data. In addition, she is also a data science mentor to guide newcomers into the field. Her domain expertise and deep insight into the perspective of the beginner’s needs make her an excellent teacher.

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