Neo4j and Machine Learning - Full Stack Applications - Intermediate

6th July 2017 in London at CodeNode

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If you are considering using neo4j as your core database, this is the talk for you. Matt will share his team's failures and successes in building Search algorithms, text analytics, classification and machine learning to improve the ability to search documents using neo4j.

He will also briefly cover Social Networking applications, recommendation engines, graph visualisations and Java Unmanaged Extensions in neo4j.

He will point out the potential pitfalls that lie in wait and how to avoid them. What’s a good architecture and modelling pattern to work towards? Matt and his team have been using neo4j full time for 18 months and will share what has worked for them as well as sharing some of their glorious and spectacular failures.

Warning: Contains hairballs, Java, Python, React.js and Kiwis.


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Neo4j and Machine Learning - Full Stack Applications - Intermediate

Matt Wright

Matt Wright is the CTO at, a startup that aims to help build better teams using graph technology and machine learning. He's a mentor at the Barclays Techstars accelerator, and has been developing graph applications with machine learning for the last couple of years. Previously he worked in Investment Banking and helped build some of the genetic algorithms that lead to the credit crunch, but please don't hold that against him.