Interpretable Machine Learning, Causal Inference

Last update: 15/01/2019



1) https://christophm.github.io/interpretable-ml-book/

2) http://mbmlbook.com/

3) Awesome ML Interpretability: https://github.com/jphall663/awesome-machine-learning-interpretability

4) Causal Inference book: https://www.hsph.harvard.edu/miguel-hernan/causal-inference-book/?fbclid=IwAR1e8oHmrBdEbQkYNaBleTrH8YyxG_FFLRig-b0Wx6Nr58zPQiEcqu-IxdI




Courses:

1) Causal Inference (Columbia University): https://www.coursera.org/learn/causal-inference/
2) A Crash Course on Causality: https://www.coursera.org/learn/crash-course-in-causality/home/welcome
3) Causal Diagrams: https://www.edx.org/course/causal-diagrams-draw-assumptions-harvardx-ph559x