Patrick Blöbaum: Performing Root Cause Analysis with DoWhy, a Causal Machine-Learning Library

In this talk, we will introduce the audience to DoWhy, a library for causal machine-learning (ML). We will introduce typical problems where causal ML can be applied and will specifically do a deep dive on root cause analysis using DoWhy. To do this, we will lay out what typical problem spaces for causal ML look like, what kind of problems we're trying to solve, and then show how to use DoWhy's API to solve these problems. Expect to see a lot of code with a hands-on example. We will close this session by zooming out a bit and also talk about the PyWhy organization governing DoWhy.

[@frashertseng9426]

Thanks for the nice talk. The library you introduced sounds extremely practical and valuable. Definitely excited to give it a try!

[@bbianchini5263]

That is exactly what I was searching for, great explanation, great library, great questions.

[@jpleonard2000]

Are the datasets used in these examples (e.g., rca_microservice_architecture_latencies.csv) available for download somewhere?