Causal Inference and Discovery in Python: Unlock the secrets of modern causal machine learning with DoWhy, EconML, PyTorch and more Molak Aleksander
Demystify causal inference and casual discovery by uncovering causal principles and merging them with powerful machine learning algorithms for observational and experimental dataPurchase of the print…
Specifikacia Causal Inference and Discovery in Python: Unlock the secrets of modern causal machine learning with DoWhy, EconML, PyTorch and more Molak Aleksander
Demystify causal inference and casual discovery by uncovering causal principles and merging them with powerful machine learning algorithms for observational and experimental dataPurchase of the print or Kindle book includes a free PDF eBookKey Features:Examine Pearlian causal concepts such as structural causal models, interventions, counterfactuals, and moreDiscover modern causal inference techniques for average and heterogenous treatment effect estimationExplore and leverage traditional and modern causal discovery methodsBook Description:Causal methods present unique challenges compared to traditional machine learning and statistics. Learning causality can be challenging, but it offers distinct advantages that elude a purely