Causal Inference for Data Science by Aleix Ruiz de Villa: A lot of material on causal inference techniques with data science applications. I like a lot of the content, but I find the order and priorities confusing at best. Why only introduce potential outcomes in chapter 10 (following a chapter on instrumental variable regression), and not define a causal effect in the PO framework much earlier? There is a good focus on DAGs throughout, but it could have been presented in a much more guiding ...
