Code library for training causal inference deep learning models with automatic hyperparameter optimization written in Tensorflow 2.

A research-grade, 6-week masterclass in Causal Inference and Causal ML from first principles. Rebuilds d-separation oracles, propensity score IRLS engines, doubly-robust AIPW estimators, Cross-Fitting Double Machine Learning (DML), and honest causal forests from scratch in pure NumPy. Fully verified against causal truth

Causal inference for promotional targeting: who should receive the email? Five CATE estimators evaluated by Qini & SNIPS policy value on Hillstrom 2008.