Summary: Data Science with Neo4j 3.5

Course Summary

In this course, you have learned how to:

  • Set up your Neo4j Sandbox development environment for performing the hands-on exercises of this course

  • Query a database for its schema

  • Return and chart the number of node labels and relationship types using matplotlib

  • Build and plot a histogram of papers and their citations using pandas and matplotlib

  • Build a mini recommendation engine with Cypher queries to:

    • find potential collaborators for an author

    • find relevant papers about a topic for an author

  • Describe what link prediction is

  • Use the link prediction functions in Neo4j

  • Understand the challenges when building machine learning models on graph data

  • Build a link prediction classifier using scikit-learn with features derived from the Neo4j Graph Algorithms library

Next steps

There are many resources available to you for learning more about doing Data Science with Neo4j.

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