double machine learning — 2 Technical Articles

Jul 14, 2025 · Artificial Intelligence

Why Causal Inference Matters: From Theory to Real-World Uplift Models

This article explains the fundamentals of causal inference, distinguishes it from correlation, introduces major theoretical frameworks such as structural causal models and potential outcomes, and demonstrates practical uplift modeling techniques—including meta‑learners, double machine learning, and deep causal networks—through a financial credit‑limit use case.

Uplift Modelingcausal inferencedouble machine learning

0 likes · 17 min read

Why Causal Inference Matters: From Theory to Real-World Uplift Models

DataFunSummit

May 25, 2024 · Artificial Intelligence

Debiased Deep Learning and Double Machine Learning for Multi‑Experiment Causal Inference

This article presents a novel approach that combines debiased deep learning with double machine learning to estimate and infer average treatment effects across multiple simultaneous online experiments, detailing problem definition, a semi‑parametric theoretical framework, and extensive field‑experiment validation on a large video‑platform dataset.

ATE estimationcausal inferencedeep learning

0 likes · 11 min read

Debiased Deep Learning and Double Machine Learning for Multi‑Experiment Causal Inference