InfoQ Homepage Presentations Reasoning about Uncertainty at Scale
Reasoning about Uncertainty at Scale
18:53
Summary
Max Livingston presents 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.
Bio
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 the jump to data science. Prior to Freebird, Max worked as a data scientist at Knewton.
About the conference
PAPIs is the conference made by and for ML practitioners. Anyone can submit talk proposals (blind-reviewed by our committee) or ask questions to take discussions further. Breaks between sessions are perfect to get to know fellow attendees, speakers, and top ML companies.
Jan 20, 2019