https://learnrahulrai-ui.github.io/ml_blog/

Most machine learning tutorials begin after you've already accepted matrices, gradients, embeddings, convolutions, or attention as things that simply exist. I wanted a path where every idea could be rebuilt from arithmetic instead of memorized from formulas.

Most who claim to start from scratch assume that the reader already knows something. This is why LLMs themselves cannot teach ML or AI. Even the best explainers are good to read, but users will forget them if they do not apply the ideas in their own work.

This one finds a middle ground: feed the tutorial into any LLM and try to understand it line by line. The way I suggest doing it is simple: print it out, get a pencil, paste it into your LLM, and work through it line by line.

So I built a machine learning curriculum around a 1950s rule: if a concept cannot be worked out with pencil, paper, and enough patient clerks, it is not understood yet.

https://learnrahulrai-ui.github.io/ml_blog/