We've recently collaborated with Databricks to create a solution accelerator for causal machine learning in their ecosystem. Learn how to leverage tools like MLFlow to facilitate model management in the context of an end-to-end causal machine learning application, taken from data exploration and causal discovery all the way to individualized policy recommendations.
EconML’s Doubly Robust Learner model jointly estimates the effects of multiple discrete treatments.
EconML’s DML estimator uses price variations in existing data, estimates individualized responses to incentives.
EconML’s DRIV estimator uses this experimental nudge to interpret experiments with imperfect compliance
Beyond predictive models: The causal story behind hotel booking cancellations.
Estimating the effect of a member rewards program.
Introducing the do-sampler for causal inference.
Understanding the question of why.
Predict causal effect from the intervention.