Please log in to watch this conference skillscast.
In this talk you’ll explore powerful analytic techniques for graph data. Firstly you’ll discover some of the innate properties of (social) graphs from fields like anthropology and sociology. By understanding the forces and tensions within the graph structure and applying some graph theory, you’ll be able to predict how the graph will evolve over time. To test just how powerful and accurate graph theory is, you’ll also be able to (retrospectively) predict World War 1 based on a social graph and a few simple mechanical rules. Then you’ll see how graph matching can be used to extract online business intelligence (for powerful retail recommendations). In turn you’ll apply these powerful techniques to modelling domains in Neo4j and show how Neo4j can be used to drive business intelligence. Don’t worry, there won’t be much maths :-)
YOU MAY ALSO LIKE:
- Real-Time Fraud Detection with Graphs (SkillsCast recorded in March 2016)
- Applied Domain-Driven Design — Full-Stack Event Sourcing (in Online Event on 9th July 2020)
- Retrospectives Antipatterns — Team Meetings That Don't Suck (in Online Event on 16th July 2020)
- Digital Discrimination: Cognitive Bias in Machine Learning (SkillsCast recorded in June 2020)
- Using A.I. to Help Humanitarian Causes (SkillsCast recorded in May 2020)
A Little Graph Theory for the Busy Data Scientist
Dr. Jim Webber is Chief Scientist with Neo Technology, the company behind the popular open source graph database Neo4j, where he works on R&D for highly scalable graph databases and writes open source software. His proven passion for microservices ecosystems and REST translate into highly engaging workshops that foster collaboration and discussion.