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Workshop: Data Science & Machine Learning with Neo4j

Although Neo4j is often used 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.

Level : Intermediate

Audience: Developers, DBAs, Business Analysts, Data Scientists, and students.

Prerequisites: You will need some familiarity with Neo4j and the Cypher language in particular. The material from the Neo4j Basics Workshop or the online Introduction to Neo4j Training should be sufficient knowledge to understand this workshop.


Mark Needham – Neo4j

Mark is a graph advocate and Developer Relations Engineer for Neo4j, the leading graph platform. He previously spent time working as a field engineer helping customers embrace graph data and Neo4j, building sophisticated solutions to challenging data problems. Co-author of the book Graph Algorithms: Practical Examples in Apache Spark and Neo4j, he also writes about his experiences of being a graphista on a popular blog