Explore advanced causal inference techniques in this 35-minute conference talk from the Data Science Festival. Delve into the world of estimating action impacts, a powerful analytical approach gaining recent attention. Learn how causal inference differs from classic supervised machine learning and why specialized techniques are necessary. Discover the auto-causality package, which leverages open-source libraries from Microsoft to automate model selection and result visualization. Follow along as the speaker demonstrates a practical application of auto-causality in analyzing real A/B test results from Wise's feature testing and CRM campaigns. Gain insights into measuring not just average impact, but also understanding which customers respond better to different options.
Overview
Syllabus
Advanced causal inference made simple
Taught by
Data Science Festival