Sign up for our newsletter and get the latest big data news and analysis.

Video Highlights: Improving ML Systems Beyond First A/B Test

Presented by Vijay Pappu, Senior ML Engineering Manager, Personalization Lead at Peloton, this talk focuses on any ML systems that rely on a feedback loop for improvement. How do we measure the efficacy of an ML system? Improving ML models offline beyond the first A/B test can be achieved in several ways: feature engineering, complex models, larger datasets. He also shares that cohort analysis could potentially improve online metrics and more.

Sign up for the free insideBIGDATA newsletter.

Join us on Twitter: @InsideBigData1 – https://twitter.com/InsideBigData1

Leave a Comment

*

Resource Links: