CRF and probability tutorial / explanation / presentation
I really should resurrect my link DB.
Sandeep Aparajit: Tutorial: Conditional Random Field (CRF) is a nice 108-page presentation spanning basic probability theory and flowing to Bayes, marginals, CRF etc etc, very very self-contained.
To read / stack
Library for debugging ml stuff
Overview — ELI5 0.9.0 documentation “.. is a Python package which helps to debug machine learning classifiers and explain their predictions.”