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Friday, September 21 • 1:30pm - 5:00pm
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Although Neo4j is often using by application developers, there's a growing trend of data scientists using graphs to help with their work.

In this session we'll look at how to combine Neo4j and the Cypher query language with the Python data science stack including libraries such as Pandas and matplotlib.

We'll look at how to do exploratory data analysis as well as find insights into networked datasets using the newly released graph algorithms package through the use of hands on tutorials.

* All workshops are hands-on. Please bring your own laptop and charger to training day. Pre-register for the workshops you'd like to attend by clicking "Add to My Sched"

avatar for Amy Hodler

Amy Hodler

Analytics and AI, Neo4j
Amy manages the Neo4j graph analytics programs and marketing. She loves seeing how our ecosystem uses graph analytics to reveal structures within real-world networks and infer dynamic behavior.In her career, Amy has consistently helped teams break into new markets at startups and large companies including EDS, Microsoft and Hewlett-Packard (HP). She most recently comes from Cray Inc., where she was the analytics and artificial... Read More →
avatar for Mark Needham

Mark Needham

Developer Relations Engineer, Neo4j
Mark Needham is a graph advocate and developer relations engineer at Neo4j.As a developer relations engineer, Mark helps users embrace graph data and Neo4j, building sophisticated solutions to challenging data problems. Mark previously worked in engineering on the clustering team... Read More →
avatar for Lauren Shin

Lauren Shin

Developer Relations, Neo4j
Lauren is excited to help facilitate the graph developer community as a student intern at Neo4j. Her studies at UC Berkeley lie in the intersection between math and computer science and she is passionate about increasing the accessibility of technical knowledge to all learners. The... Read More →

Friday September 21, 2018 1:30pm - 5:00pm EDT
Liberty Room Marriott Marquis, 8th Floor
  Workshop, AI and Machine Learning