An introduction to machine learning on graphs
Who is this presentation for?
- Engineers and machine learning researchers
Graphs are a powerful way to represent knowledge. They can represent disparate types of knowledge in one unified structure. Organizations, in fields such as biosciences and finance, are starting to amass large knowledge graphs, but they lack the machine learning tools to extract insights from them.
David Mack offers an overview of what insights are possible and surveys the most popular approaches. Along the way, he points out areas of active research and shares online resources and a bibliography for further study.
- A basic understanding of neural networks
What you'll learn
- Learn how to get started with machine learning on graphs
David Mack is a founder and machine learning engineer at Octavian.ai, exploring new approaches to machine learning on graphs. Previously, he cofounded SketchDeck, a Y Combinator-backed startup providing design as a service. He holds an 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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