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 for optimizing fast management, storage, and traversal of nodes and relationships.

You can use it for artificial intelligence, fraud detection, graph-based search, network ops & security, and many other use cases. Graph algorithms which are included in Neo4j’s growing and open library.In this course, you will cover the important graph algorithms which are used in Neo4j’s graph analytics platform. This will be an engaging and practical course, where you will explore various high-performance graph algorithms that help reveal hidden patterns and structures in your connected data. You will learn how to master your skills to use the algorithms efficiently to understand, model and predict complicated dynamics. You will also be able to develop and deploy graph-based solutions faster and have streamlined workflows as well as solve real-world problems. With the help of this course, you will learn how to make your work easier by selecting the right algorithm based on your requirement, understand its workings and implement it.

By the end of the course, you will be familiar and confident with the graph analytics with Neo4j to deal with a broad range of problems and learn to use its quick insights to wield powerful results.

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

Style and Approach

This course uses real-world scenarios to introduce each concept. Using illustrative examples taken from various fields, from routing to social media to recommendation engines, this course gives you all the tools you need to use this library in your daily work.

Publication date:
April 2019
2 hours 20 minutes

About the Author

  • Estelle Scifo

    Estelle Scifo has more than 7 years’ work experience as a data scientist. 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. Besides that, she is also a data science mentor to guide newcomers into the field. The domain expertise and the beginner’s mind make her an excellent teacher.

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