Introduction to Graph Algorithms in Neo4j 4.x: Summary

Summary

You can now:

  • Describe how Neo4j supports graph algorithms for analysis and machine learning.

  • Describe the components of the Neo4j Graph Data Science library.

  • Set up your environment for running graph algorithms.

  • Describe the workflow you use to use the Graph Data Science library.

  • Determine memory requirements for your analysis.

  • Use Community Detection algorithms.

  • Use Centrality algorithms.

  • Use Similarity algorithms.

  • Perform data analysis using a set of graph algorithms.

  • Describe some best practices for using algorithms.

Resources

Here are some Graph Data Science-specific resources:

There are many resources available to you for learning more about Neo4j and Cypher.

Next Steps

Now that you have completed the Introduction to Graph Algorithms in Neo4j 4.x Course, you can take any of these other Graph Data Science courses:

Using a Machine Learning Workflow for Link Prediction

Applied Graph Data Science for Web Applications

Neo4j Graph Data Science Certification

Take the Neo4j Graph Data Science Certified exam to gain your certificate. This certification exam tests you on content from the courses in the Introduction to Graph Algorithms in Neo4j 4.x. You can take the certification exam multiple times until you pass!

Take the Neo4j Graph Data Science Certification exam

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