Abstract: There is no doubt that machine learning and graphs go hand in hand — and Neo4j makes it possible to take machine learning to the next level. In this presentation, we'll share how CluedIn built Neo4j into a decision engine that turns company data into actionable insights. By using machine learning techniques and the graph as a decision tree, we were able to achieve amazing precision in merging and identifying insights in the enterprise. With practical demos and techniques, viewers will leave this presentation with new and effective ways of working with Neo4j.
Bio: Tim has been spending the last 5 years of his career focussing on building large scale applications for the enterprise. With focus on scaling, performance, machine learning and databases, he brings with him over 10+ years of software experience. Being a Neo4j developer for the last 5-6 years of his career, he has a main focus on using database technologies like the graph to solve very complex and large scale problems.
CEO and Co-Founder of CluedIn ApS