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.
Prerequisites
This course is intended for analysts and data scientists who have basic knowledge of:
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
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Graph algorithm execution patterns
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Different categories of graph algorithms and common use cases for each
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How to run graph native machine learning pipelines in GDS
