pymc-labs
add info about related packages and learning resources
Packages
- https://github.com/bernardodionisi/differences
- https://github.com/py-why/dowhy
- https://github.com/amaiya/causalnlp
Books
- [draft] https://alexdeng.github.io/causal/, https://alexdeng.github.io, Alex Deng
- [not yet available book] https://alxndr.io, Aleksander Molak
- [in progress at Manning] https://www.manning.com/books/causal-inference-for-data-science, Aleix Ruiz de Villa
- [in progress at Manning] https://www.manning.com/books/causal-machine-learning, Robert Ness
Top-tier blog posts
- https://emilyriederer.netlify.app/post/causal-design-patterns/, Emily Riederer
Is this still open. Do you have anywhere specific you want this info to be presented?
Still open 👍🏻
Initially I was maybe a bit ambitious. I think we should not try to make this an exhaustive list of causal inference resources. There is already the Awesome Causal Inference curated list by @matteocourthoud.
Instead, maybe we should restrict it to directly related packages and books.
How about a new page under the knowledge base section? We should probably reference the Awesome Causal Inference repo as an example of a more complete list of resources but then go on to list directly relevant resources?
Yeah sounds good. Adding to the section now. Question though do have preference to directly relevant resources. I Know the package was inspired by Quasi-Experimentation: A Guide to Design and Analysis Charles S. Reichardt. Unless im mistaken. So, that's obvious one.