.. _guide: :parenttoc: True User Guide ========== .. toctree:: :maxdepth: 2 :numbered: The basics of double/debiased machine learning Data Backend Models Heterogeneous Treatment Effects Score functions Double machine learning algorithms Learners, hyperparameters and hyperparameter tuning Variance estimation and confidence intervals Sample-splitting, cross-fitting and repeated cross-fitting Sensitivity Analysis