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Wednesday, October 17 • 11:30am - 11:50am
Reasoning About Uncertainty at Scale

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Freebird models US domestic flights in a way that captures uncertainty at every step. We present a case study of using Bayesian modelling and inference to directly model behavior of aircraft arrivals and departures, focusing on the uncertainty in those predictions. Along the way we will discuss theoretical considerations, highlighting what can go wrong, while emphasizing practical implications around scaling to large data sets.
Speakers
ML

Max Livingston

Data Scientist, Freebird
Max Livingston is a data scientist at Freebird, where he uses Bayesian machine learning techniques to model flight disruptions and last-minute prices. He graduated from Wesleyan University with high honors in Economics and worked in the Research group of the New York Fed before making... Read More →

Wednesday October 17, 2018 11:30am - 11:50am
Horace Mann
  New ML techniques

Attendees (48)