Sean Taylor — Business Decision Problems
Podcast: Gradient Dissent: Conversations on AIPublished On: Thu May 13 2021
Description: Sean joins us to chat about ML models and tools at Lyft Rideshare Labs, Python vs R, time series forecasting with Prophet, and election forecasting.---Sean Taylor is a Data Scientist at (and former Head of) Lyft Rideshare Labs, and specializes in methods for solving causal inference and business decision problems. Previously, he was a Research Scientist on Facebook's Core Data Science team. His interests include experiments, causal inference, statistics, machine learning, and economics.Connect with Sean:Personal website: https://seanjtaylor.com/Twitter: https://twitter.com/seanjtaylorLinkedIn: https://www.linkedin.com/in/seanjtaylor/---Topics Discussed:0:00 Sneak peek, intro0:50 Pricing algorithms at Lyft07:46 Loss functions and ETAs at Lyft12:59 Models and tools at Lyft20:46 Python vs R25:30 Forecasting time series data with Prophet33:06 Election forecasting and prediction markets40:55 Comparing and evaluating models43:22 Bottlenecks in going from research to productionTranscript:http://wandb.me/gd-sean-taylorLinks Discussed:"How Lyft predicts a rider’s destination for better in-app experience"": https://eng.lyft.com/how-lyft-predicts-your-destination-with-attention-791146b0a439Prophet: https://facebook.github.io/prophet/Andrew Gelman's blog post "Facebook's Prophet uses Stan": https://statmodeling.stat.columbia.edu/2017/03/01/facebooks-prophet-uses-stan/Twitter thread "Election forecasting using prediction markets": https://twitter.com/seanjtaylor/status/1270899371706466304"An Updated Dynamic Bayesian Forecasting Model for the 2020 Election": https://hdsr.mitpress.mit.edu/pub/nw1dzd02/release/1---Get our podcast on these platforms:Apple Podcasts: http://wandb.me/apple-podcastsSpotify: http://wandb.me/spotifyGoogle Podcasts: http://wandb.me/google-podcastsYouTube: http://wandb.me/youtubeSoundcloud: http://wandb.me/soundcloudJoin our community of ML practitioners where we host AMAs, share interesting projects and meet other people working in Deep Learning:http://wandb.me/slackCheck out Fully Connected, which features curated machine learning reports by researchers exploring deep learning techniques, Kagglers showcasing winning models, industry leaders sharing best practices, and more:https://wandb.ai/fully-connected
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