Part 1: Causality – an Introduction
Part 1 of this book will equip us with a set of tools necessary to understand and tackle the challenges of causal inference and causal discovery.
We’ll learn about the differences between observational, interventional, and counterfactual queries and distributions. We’ll demonstrate connections between linear regression, graphs, and causal models.
Finally, we’ll learn about the important properties of graphical structures that play an essential role in almost any causal endeavor.
This part comprises the following chapters:
