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

Generative VS Discriminative Models - Prathap Manohar Joshi - Medium

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.”