In this episode, we will explore Urban Company’s business needs and the role of causal machine learning in addressing them. We will delve into three key models—S-learner, T-learner, and X-learner—and used a simple example to illustrate how each one works. These models provide valuable insights by offering more accurate estimates of cause-and-effect relationships, helping companies make better data-driven decisions.

For more details, you can refer to their published tech blog, linked here for your reference: https://medium.com/uc-engineering/how-urban-company-leverages-causal-inference-to-power-data-driven-decisions-a339cfcaa0e2