An introduction to the emerging fusion of machine learning and causal inference. The book presents ideas from classical structural equation models (SEMs) and their modern AI equivalent, directed acyclical graphs (DAGs) and structural causal models (SCMs), and covers Double/Debiased Machine Learning methods to do inference in such models using modern predictive tools.

翻译：本书介绍了机器学习与因果推断这一新兴融合领域。书中阐述了经典结构方程模型及其现代人工智能等价物——有向无环图与结构因果模型的基本思想，并涵盖了利用现代预测工具在这些模型中进行推断的双重/去偏机器学习方法。