// the find
mrdbourke/machine-learning-roadmap
A roadmap connecting many of the most important concepts in machine learning, how to learn them and what tools to use to perform them.
A 2020-era visual mindmap linking ML concepts, tools, and learning resources. Aimed at beginners trying to orient themselves in the ML landscape before committing to a learning path. Not a tutorial or a course — just a map.
The visual overview gives beginners a genuine sense of how the pieces connect — math, tools, problem types, process — rather than just a flat list of topics. The companion YouTube walkthrough is unusually thorough for a reference repo. The mindmap format is actually well-suited to this use case: you can see where you are and where you're going.
Last updated in 2022 and the author admits it's a 2020 roadmap — no coverage of LLMs, transformers-in-practice, or the modern Python stack (nothing about Hugging Face, PEFT, vLLM, etc.). The repo is essentially a PNG and a PDF; there's nothing interactive or maintainable here, so it will only get staler. No code, no exercises, no checkpoints — it's inspiration, not instruction.