What it is
The machine-learning cards I wrote for myself while studying the field properly: supervised learning, bias–variance, regularisation, trees and ensembles, neural networks and backprop, CNNs, sequence models, attention and transformers, plus the probability that underpins it all.
The philosophy
One idea per card, short prompts, derivations broken into steps you can actually recall at a whiteboard. These are paraphrased understanding — not textbook sentences with cloze deletions punched in.
Pairs well with
The CS Interview Prep bundle for the software side of ML interviews.