Abstract:

What use is machine learning unless we can turn predictions into decisions? In this talk I’ll explain how this idea motivates our strategy at PROWLER.io. I’ll explain how different research teams at the company are attacking different parts of decision theory, and focus on outputs from the probabilistic modelling team. I’ll show how probabilistic models are used for forecasting in smart cities, and examine some of the machine learning advances we’ve made to achieve this.

Short Bio:

James Hensman is the head of probabilistic modelling at PROWLER.io. He was previously a Lecturer at Lancaster University, where he held a MRC fellowship in Biostatistics. He obtained his PhD from Sheffield University, where he studied engineering. His interests are in statistical machine learning including Gaussian process models; he co-founded the GPy and GPflow packages.