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Ask HN: How to learn AI from first principles?

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Re: Ask HN: How to learn AI from first principles?

#25
In the coursera course accompanying the statlearning book he starts with introducing a nearest neighbour algorithm and from that he develops a linear regression.

I think that is "first principals of AI". Like, what does it even mean when we ask an algorithm to "learn" from data?

Re: Ask HN: How to learn AI from first principles?

#28
Hi, it depends on what you mean by "first principles".

If you don't have a solid background in math, then that's what you should improve upon (calculus, linear algebra, discrete math, probability theory, information theory). Some of the books you mention do cover this at the beginning, but most people take separate courses on these topics at University, with lots of homework, etc.

Also, the first book on your list is the classic textbook by Norvig, but I don't think it's actually very good. I remember reading it in my college AI course 25 years ago and it was painful back then (anybody remember "wumpus"?). It's a big book that covers too much, it's like printing out a lot of Wikipedia pages. You're better off finding books with smaller scope that focus on something you actually care about / is relevant to the way the field has developed.

Re: Ask HN: How to learn AI from first principles?

#30
Back in 2018 I did Andrew Ng's course in Machine Learning on Coursera. It was pretty much "from first principles" in that you learned a bit of linear algebra and then you implemented algorithms in Octave, working up to MNIST etc. I felt like I came out of it with a good understanding of the basics, and that ML is maths not magic.

Looks like the course has turned into a multi-course "specialization" and I have no idea if any of it is the aame as the course I did. But it might be a place to start.

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