Michael Hunger has been passionate about software development for a very long time.
For the last few years, he has been working on the open source Neo4j graph database filling many roles. As caretaker of the Neo4j community and ecosystem, he especially loves to work with graph-related projects, users, and contributors.
As a developer Michael enjoys many aspects of programming languages, learning new things every day, participating in exciting and ambitious open source projects and contributing and writing software related books and articles.
Build a real-time recommendation engine from the ground up. Using a real life dataset from meetup.com combined with a content-based and collaborative filtering to develop a multi-faceted recommendation engine. This training also covers how to make modeling decisions based on the types of questions being asked of the data and how to optimize your model and queries for maximum performance. We will import the meetup data into Neo4j, and start building the recommender step by step by adding scorers for the different aspects of the data. Partly personalization happens by interest, partly by peer group or location.