The relationship between causality and artificial intelligence can be seen from two points of view: how causality can help solve some of the current problems of AI and how causal inference can leverage machine learning techniques. In this course we will review the two points of view with special emphasis on examples and practical cases.
- Observational and Interventional Distributions. Causal Thinking | Slides
- Potential Outcomes and the Fundamental Problem of Causal Inference | Slides
- Causal Graphs | Slides
- Estimand-based Estimation: Metalearners | Slides
- Estimand-agnostic Estimation: Counterfactuals | Slides
- Causal Machine Learning (Supervised Learning) | Slides
- Causal Machine Learning (Reinforcement Learning) | Slides
- Practical Causal Inference | Notebooks