Causal Inference for Machine Learning Engineers

A significant portion is dedicated to integrating causal inference with deep learning, introducing architectures such as TARNet, CFRNet, and DragonNet, as well as frameworks like Double Machine Learning, all designed to address the challenges of high-dimensional data and improve causal effect estimation in complex settings.