Textbook recommendations covering machine learning techniques for causal inference? Over the past 15 years there has been progress in adapting machine learning methods for causal inference. For example: targeted learning, double machine learning, causal trees.
Is there a textbook that covers the current range of techniques? I haven't seen anything on Amazon, perhaps there are texts available on other sites? Or will be published soon?

I follow this area pretty closely, but I think this subfield is so new no textbook exists (yet).
However, there are some course videos that are fairly good:

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*Machine Learning & Causal Inference: A Short Course at Stanford (accompanying tutorial)

*Summer Institute in Machine Learning in Economics (MLESI21) at University of Chicago

There is also a nice survey paper:
"Machine learning methods that economists should know about"
by Susan Athey, Guido Imbens in the Annual Review of Economics (link to draft)
