BT

InfoQ Homepage Presentations Reasoning about Uncertainty at Scale

Reasoning about Uncertainty at Scale

Bookmarks
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.

Recorded at:

Jan 20, 2019

Hello stranger!

You need to Register an InfoQ account or or login to post comments. But there's so much more behind being registered.

Get the most out of the InfoQ experience.

Allowed html: a,b,br,blockquote,i,li,pre,u,ul,p

Community comments

Allowed html: a,b,br,blockquote,i,li,pre,u,ul,p

Allowed html: a,b,br,blockquote,i,li,pre,u,ul,p

BT

Is your profile up-to-date? Please take a moment to review and update.

Note: If updating/changing your email, a validation request will be sent

Company name:
Company role:
Company size:
Country/Zone:
State/Province/Region:
You will be sent an email to validate the new email address. This pop-up will close itself in a few moments.