In the course of preparing several ML-related courses, I compiled a short handout containing:
- useful things to know (and hard to find in one place) when entering into Machine Learning (and especially Deep Learning) field,
- how to avoid common pitfalls.
Its format is inspired by Cornell’s note-taking method, containing short questions and (slightly longer) answers, with additional space left for the summary/notes. To obtain a copy, just click the button below: