> This is a draft workshop to build from scratch the basic background needed to try introductory books and courses in AI and how to optimize their deployments.
I'm not sure learning the things on that page – Peano axioms, basic real analysis, etc. – really helps with deploying AI. I know plenty of talented graduate students with papers at NeurIPS, ICML, and another top conferences who don't know a lick of set theory, so certainly it's not necessary, even for highly academic work.
Based on my experience and what we know about the psychology of learning, I'd recommend finding a motivating ML project or application (e.g. point the phone at a sudoku and it overlays the solution), and then working backwards to figure out what you need to know to implement it. Probably it will not be the Peano axioms.
> This is a draft workshop to build from scratch the basic background needed to try introductory books and courses in AI and how to optimize their deployments.
I'm not sure learning the things on that page – Peano axioms, basic real analysis, etc. – really helps with deploying AI. I know plenty of talented graduate students with papers at NeurIPS, ICML, and another top conferences who don't know a lick of set theory, so certainly it's not necessary, even for highly academic work.
Based on my experience and what we know about the psychology of learning, I'd recommend finding a motivating ML project or application (e.g. point the phone at a sudoku and it overlays the solution), and then working backwards to figure out what you need to know to implement it. Probably it will not be the Peano axioms.