These are some of my notes for various stats and ML lectures. The stats lectures are a bit more introductory and the ML lectures are a bit more advanced. Some of the ML lectures contain lab components in Jupyter notebooks, on what I thought would be most interesting/relevant for that topic. I particularly like the eigenface lab.