With more than 9 million users and 21 million repositories, Github is the world's biggest code sharing platform. Its API offers a window to the public activity of about 600.000 events a day.
In this talk you will discover how this amount of user activities transformed in a suitable graph can become a new source of knowledge.
A demonstration of how Neo4j and machine learning algorithms built on top of it can leverage this tremendous amount of hidden valuable real-time data to gain new insights, offering new application possibilities, from recruitment to social network analysis and recommendations.
The talk will cover topics like data pipelines to Neo4j, technical challenges, algorithms and application ideas you can build around this kind of platforms.
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Empowering Github Social with Neo4j
Christophe is an expert on the Neo4j graph database and the Cypher query language. He is a skilled software engineer who has been involved in many Neo4j projects optimising complex Cypher queries, building enterprise-grade graph-based recommendation engines and developing search tools combining Neo4j and the Elastic Stack. He is also the author of the most popular PHP driver for Neo4j, the GraphAware PHPclient, Reco4PHP (a Neo4j based Recommendation Engine Framework) as well as GraphAware GraphGen, an open-source web-based tool for generating graphs. Christophe is based in Bruges, Belgium, and speaks fluent Dutch, French and English.