About this video

Neo4j is an open source, highly scalable, and transactional graph database well-suited to connected data. It is the world's leading graph database management system, which is designed to optimize the fast management, storage, and traversal of nodes and relationships. Neo4j can be utilized for artificial intelligence, fraud detection, graph-based search, network ops and security, and many other use cases. There are numerous graph algorithms in Neo4j’s growing and open library which the users can use for their projects.

Delivered by a PhD-educated physicist whose academic work incorporated collaboration with CERN, this course will cover the important graph algorithms that are used in Neo4j’s graph analytics platform. This is an engaging and practical course, through which you’ll explore various high-performance graph algorithms that reveal hidden patterns and structures in your connected data. You’ll master these skills to use the algorithms efficiently, and to understand, model, and predict complicated, but important, dynamics and interrelationships.

You’ll also be able to develop and deploy graph-based solutions more quickly, apply streamlined workflows, and solve real-world problems. With the help of this course, you’ll learn how to make your work easier by selecting the right algorithm based on your requirements, understand its workings, and implement it.

By the end of the course, you’ll be familiar and confident with graph analytics using Neo4j and will be able to deal with a broad range of problems, using its rapid insights to wield powerful results.

The code bundle for this course is available at - https://github.com/PacktPublishing/Exploring-Graph-Algorithms-with-Neo4j

Publication date:
April 2019
2 hours 20 minutes

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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