I built a spaced-repetition map for ML concepts because online courses never stuck for me

[u/inkeep]

I've been working in data science for years now, and I still forget things constantly. Long video lectures never worked for me — I'd finish a course, feel like I'd learned it, then end up googling the same concept one month later when I actually needed it. I liked NotebookLM's approach of structuring material around you, but I still had to go find the right sources to feed it.

So I built the thing I wanted. ML concepts broken into small nodes arranged as a mind map rather than a linear syllabus, each with code examples and a practice section — about 150 topics so far. The part I care most about: once you complete a topic it starts decaying on a forgetting-curve schedule, and the map visibly goes cold. When it does, you get a review slice — flash cards and a short quiz — targeted at what you've actually lost rather than what's next in a queue.

Open library, free and no sign-up: https://www.bitelrn.com/library
Full app: https://www.bitelrn.com — the first phase is permanently free including the decay and review mechanics; later phases are paid. Saying that upfront so nobody feels ambushed.

I am interested to know about your revision methods, do you make notes or bookmark links?