Learn how to use the Neo4j Graph Data Science Library in a Machine Learning workflow to link prediction

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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:

  • Cypher

  • Experience with the Graph Data Science Library

  • 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

  • How to set up your Neo4j development environment to run Jupyter Notebooks.

  • How to perform steps to explore a dataset.

  • Incorporate graph algorithms into your code to provide recommendations from the data.

  • Incorporate link prediction algorithms into your code.

  • The challenges of building a Machine Learning model.

  • Build a link prediction classifier using scikit-learn.

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