Graph Technology and Data Science Workshop

By Neo4J 

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Time and Location

Sep-9, 2022 at 9:00am - 3:00pm EDT

The Westin Atlanta Perimeter North

Workshop Summary

Curious as to what graph data science (GDS) is all about? Come get a refresher on graph, graph data science, and how you can get value out of the connections in your data! This workshop will provide you with a crash course in how to leverage graphs within your data science workflows. The hands-on section focuses on providing concrete examples of how to interact with the Neo4j database from a python notebook, create graph-y features, train an ML model, and then use graph visualization tools to communicate results to other teams. Newbies to graph data science as well as experienced graph practitioners are welcome to join and hear the latest developments in the Neo4j GDS Library.

Agenda:

9am-3pm

  • Introduction

    • Graph Technology and Graph Data Science

  • Graph Data Science Deep Dive

    • Value Proposition -  Why should you care?

    • Graph Algorithms

    • Why Neo4j GDS?

  • Real-world applications of Graph Data Science

    • Context-aware Recommender systems

    • Entity resolution/Identity resolution

    • Fraud detection and investigation

  • Graph-powered Machine Learning (Hands-on tutorials)

    • Graph algorithms and Machine learning for Fraud Detection (Python/Neo4j GDS library)

    • Representation learning on graphs (Neo4j GDS library)

    • Graph visualization (Neo4j Bloom)

  • Graph Data Science in Production

    • Deployment options

    • Best Practices Q&A


Prerequisites:

 

Additional Resources

 

Who Should Attend:
  • Anyone with a desire to learn more about graph data science!

 

Who Should NOT Attend:
  • If you are looking for a deep dive conversation into your existing GDS pipeline - please set up some 1:1 time with one of our experts by emailing -> gds_experts@neotechnology.com 

 

About the Instructor: 

PHANI DATHAR Ph.D., Data Science Solution Architect, Neo4j

Phani Dathar is a computational scientist and holds a PhD in Nanotechnology and Computational Materials Science from Louisiana Tech University. After a decade of research in batteries and electrical energy storage in both industry and academia, he transitioned to a career in data science and machine learning and since worked with early-stage start-ups in AI/ML space and large organizations like American Airlines and Infosys as a data science consultant. He enjoys helping prospects and customers get started with Graph Data Science and was instrumental in launching Neo4j’s Graph Data Science training courses.