An introduction to machine learning on graphs
Who is this presentation for?Engineer / Machine learning researcher
Graphs are a powerful way to represent knowledge. They can represent disparate types of knowledge in one unified structure. Organizations (in fields such as bio-sciences and finance) are starting to amass large knowledge graphs, but lack the machine-learning tools to extract the insights they need from them.
In this presentation, I’ll give an overview of what insights are possible and survey the most popular approaches. I’ll also point out the areas of active research. Finally, I’ll provide thorough online resources and bibliography for the audience to use in their work.
This talk is based on recent articles and talks I’ve worked on with my colleague Andy:
Prerequisite knowledgeNeural networks basics
What you'll learn
David is a founder and machine learning engineer at Octavian.ai, exploring new approaches to machine learning on graphs
Previously he co-founded of SketchDeck, a Y-Combinator backed technology startup providing design as a service. He has a MSci in Mathematics and the Foundations of Computer Science from the University of Oxford and a BA in Computer Science from the University of Cambridge.
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