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Neo4j Live Demo: 5 Graph Data Science Basics For Improving Predictions
10:00 a.m. PT | 1:00 p.m. ET | 18:00 BST | 19:00 CEST
Commercial applications of graph data science are new, and most data science teams are still getting up to speed on how to best use the approach in their work.
Graph data science brings together graph analytics, statistics, and AI and machine learning techniques to improve predictions and ML models. This quick overview will walk you through the basics of graph data science so that you feel confident knowing when to use it and why.
During this 30-minute session, experts will answer:
How is graph data science different from traditional data science techniques?
What are the questions graph data science helps answer?
Who uses graph data science?
Register today to learn the basics of graph data science!
Technology Partner Architect, Neo4j
David Allen is Technology Partner Architect at Neo4j. He is a deeply technical generalist with experience in managing teams and driving towards complex goals. The most fun he has had in his career is when he is learning something new, or trying to figure out how to do something that hasn’t been done before.
When not trying to improve something technical, you can usually find David playing guitar or cycling. He loves meeting new people, and has a very keen interest in language and culture and loves to find common ground with other people through travel and music.
Partner Technical Marketing, Neo4j
Jaime is from the Technology Partner team at Neo4j, with a seasoned career successfully executing channel and product campaigns across industries, geographies and technologies. He has “led the charge” for a number of SaaS, Advanced Analytics and AI solutions from start-ups to larger Enterprise Fortune 200 companies, such as IBM, Oracle and EMC among others. As a graduate of Santa Clara University, Jaime applies his technical, market and industry knowledge enabling today’s organizations to benefit from best-in-class solutions and optimized outcomes from their data.
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