Hey HN, I don’t know who else has the same issue, but:

Textbooks often bury good ideas in dense notation, skip the intuition, assume you already know half the material, and get outdated in fast-moving fields like AI.

Over the past 7 years of my AI/ML experience, I filled notebooks with intuition-first, real-world context, no hand-waving explanations of maths, computing and AI concepts.

In 2024, a few friends used these notes to prep for interviews at DeepMind, OpenAI, Nvidia etc. They all got in and currently perform well in their roles. So I'm sharing.

This is an open & unconventional textbook covering maths, computing, and artificial intelligence from the ground up. For curious practitioners seeking deeper understanding, not just survive an exam/interview.

To ambitious students, an early careers or experts in adjacent fields looking to become cracked AI research engineers or progress to PhD, dig in and let me know your thoughts.

Also I’m not sure if this is well known but Gemini has a nice quiz/test mode that you can use for learning. Ask it to quiz you on a subject and you can increase/decrease difficulty and keep going. I pair it up with textbooks as a learning tool; not in school or anything just for my own enjoyment.

It would be nice if the unfinished sections had at least an outline so others could fill in the gaps. SIMD for example… :D

Code walkthroughs and exercises are included, in Jax

Math, not Maths. You wouldn't called it Econs 101 would you?