Neo4j Graph Data Science Fundamentals
In this course, we cover the high level concepts that a Data Scientist needs to know to conduct analytics with the Neo4j Graph Data Science library (GDS). We cover the range of graph algorithms and machine learning operations available in GDS with examples of how to use them on real data.
The course automatically creates a new
movie recommendations sandbox within Neo4j Sandbox that you will use throughout the course.
This course is intended for analysts and data scientists who have basic knowledge of:
Data science fundamentals
Graph database fundamentals
This course provides code examples from the Neo4j Graph Data Science library (GDS). If you haven’t already done so, we recommend you take the Introduction to Neo4j Graph Data Science course to find out how these procedures work.
What you will learn
Graph algorithm execution patterns
Different categories of graph algorithms and common use cases for each
How to run graph native machine learning pipelines in GDS
Table of Contents
If you find yourself stuck at any stage then our friendly community will be happy to help. You can reach out for help on the Neo4j Community Site, or head over to the Neo4j Discord server for instant feedback.
If you have any comments or feedback on this course you can email us on email@example.com.