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April 29-30, 2018: Training
April 30-May 2, 2018: Tutorials & Conference
New York, NY

Deep dive into probabilistic machine learning

Zoubin Ghahramani (Uber | University of Cambridge)
11:05am–11:45am Tuesday, May 1, 2018
Location: Grand Ballroom East
Average rating: ****.
(4.20, 5 ratings)

What you'll learn

  • Explore probabilistic, or Bayesian, machine learning concepts and research

Description

Probability theory provides a mathematical framework for understanding learning and building rational intelligent systems. Zoubin Ghahramani explores the foundations of the field of probabilistic, or Bayesian, machine learning and details current areas of research, including Bayesian deep learning, probabilistic programming, and the Automatic Statistician. Zoubin also explains how Uber organizes AI research and where probabilistic machine learning fits in.

Photo of Zoubin Ghahramani

Zoubin Ghahramani

Uber | University of Cambridge

Zoubin Ghahramani is a professor at the University of Cambridge, where he leads the Machine Learning Group, and the chief scientist at Uber. His research focuses on probabilistic approaches to machine learning and AI. Zoubin is also deputy director of the Leverhulme Centre for the Future of Intelligence and was a founding Cambridge director of the Alan Turing Institute. In 2015, he was elected a fellow of the Royal Society.