Learn how to use the Neo4j Graph Data Science Library in a Machine Learning workflow for link prediction
About the Course
This online course is a collection of lessons and hands-on exercises that teach you how to incorporate some of the graph algorithms of the Neo4j Data Science Library into a Machine Learning workflow for link prediction.
Prerequisites
You must have the following programming experience to take this course:
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Cypher
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Experience with the Graph Data Science Library
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Python using Jupyter Notebooks
Duration
If you perform all of the hands-on exercises in this course, it will take you 4 hours to complete the course.
What you will learn
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How to set up your Neo4j development environment to run Jupyter Notebooks.
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How to perform steps to explore a dataset.
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Incorporate graph algorithms into your code to provide recommendations from the data.
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Incorporate link prediction algorithms into your code.
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The challenges of building a Machine Learning model.
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Build a link prediction classifier using scikit-learn.