Causal Inference and Discovery in Python
Author: Molak | Year: 2023
Summary Notes
- 第01章：Causality – Hey, We Have Machine Learning, So Why Even Bother?
- 第02章：Judea Pearl and the Ladder of Causation
- 第03章：Regression, Observations, and Interventions
- 第04章：Graphical Models
- 第05章：Forks, Chains, and Immoralities
- 第06章：Nodes, Edges, and Statistical (In)dependence
- 第07章：The Four-Step Process of Causal Inference
- 第08章：Causal Models – Assumptions and Challenges
- 第09章：Causal Inference and Machine Learning – from Matching to Meta-Learners
- 第10章：Causal Inference and Machine Learning – Advanced Estimators, Experiments, Evaluations, and More
- 第11章：Causal Inference and Machine Learning – Deep Learning, NLP, and Beyond
- 第12章：Can I Have a Causal Graph, Please?
- 第13章：Causal Discovery and Machine Learning – from Assumptions to Applications
- 第14章：Causal Discovery and Machine Learning – Advanced Deep Learning and Beyond
- 第15章：Epilogue