Skip to content
TrackPodcasts
technologyMar 17, 202239:57pending

An open source and end-to-end library for causal inference

About this episode

This week’s guests are Amit Sharma (Principal Researcher) and Emre Kiciman (Senior Principal Researcher) of Microsoft Research. We talk about practical applications of causal inference, a set of tools and techniques that enable data teams to draw causal conclusions based on data.  Amit and Emre are part of the team behind DoWhy, a new open source library for estimating causal effects based on historical data alone, particularly useful when we cannot run an experiment because of time, expense, or ethical concerns.

Download the FREE Report: Trends in Data, Machine Learning, and AI → https://gradientflow.com/2022trendsreport?utm_source=DEpodcast

Subscribe: AppleAndroidSpotifyStitcherGoogleAntennaPodRSS.

Detailed show notes can be found on The Data Exchange web site.

Get every episode summarized

Each time The Data Exchange with Ben Lorica publishes, we email you a written briefing from the transcript — the topics, who appeared, and any specific claims, with the ad reads skipped.

Email me new episodes

Free for 3 shows. No card needed.

Hosts & guests

No transcript yet

This episode has not been transcribed. Request it and it moves to the front of the queue.

An open source and end-to-end library for causal inference

The Data Exchange with Ben Lorica

0:00
39:57

More episodes

More from The Data Exchange with Ben Lorica

View all episodes →