Getting Started with Graph Data Science

Abstract: 

You’ve probably heard that graphs are a major trend in data science and analytics, and you may have wondered how to translate the buzz into business value. We’ll cover the fundamentals of graph data science: how graphs can be used in data science, common graph data science techniques, and how Neo4j’s connected data platform can help you move from proof of concept to production. Learn about world use cases for graph data science including fraud, recommendations, and supply chain optimization to show how it’s possible to translate state of the science techniques into practical business value across multiple industries and use cases.

Bio: 

Emil Pastor is a Solution Architect at Neo4j based in Sydney. He has been a data and AI professional enabling organisations in various industries through strategy, architecture, use case delivery, and capability building to support stakeholders and client data professionals in leveraging their data assets. Prior to working at Neo4j, he worked as an Architect and Consultant for organisations like Microsoft, McKinsey & Company (QuantumBlack), EY and Teradata.

Open Data Science

 

 

 

Open Data Science
One Broadway
Cambridge, MA 02142
info@odsc.com

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