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Bayesian A/B Testing

Bayesian A/B Testing

FromData Skeptic


Bayesian A/B Testing

FromData Skeptic

ratings:
Length:
30 minutes
Released:
Oct 23, 2015
Format:
Podcast episode

Description

Today's guest is Cameron Davidson-Pilon. Cameron has a masters degree in quantitative finance from the University of Waterloo. Think of it as statistics on stock markets. For the last two years he's been the team lead of data science at Shopify. He's the founder of dataoragami.net which produces screencasts teaching methods and techniques of applied data science. He's also the author of the just released in print book Bayesian Methods for Hackers: Probabilistic Programming and Bayesian Inference, which you can also get in a digital form.
This episode focuses on the topic of Bayesian A/B Testing which spans just one chapter of the book. Related to today's discussion is the Data Origami post The class imbalance problem in A/B testing.
Lastly, Data Skeptic will be giving away a copy of the print version of the book to one lucky listener who has a US based delivery address. To participate, you'll need to write a review of any site, book, course, or podcast of your choice on datasciguide.com. After it goes live, tweet a link to it with the hashtag #WinDSBook to be given an entry in the contest. This contest will end November 20th, 2015, at which time I'll draw a single randomized winner and contact them for delivery details via direct message on Twitter.
Released:
Oct 23, 2015
Format:
Podcast episode

Titles in the series (100)

Data Skeptic is a data science podcast exploring machine learning, statistics, artificial intelligence, and other data topics through short tutorials and interviews with domain experts.