I'm interested in getting into this field but there are so many books out there discussing specific areas (Keras, Tensorflow, NumPy, LLMs, oh my) that it's difficult to know where to start.
I have an undergrad statistics degree from 15 years ago, and remember a good bit of it, but could use some math refreshers. I don't mind brushing off the cobwebs but could definitely use a hand in doing so.
A lot of the more technical books regarding the subject feel like they're published by Springer and are aimed at graduate research, way beyond my understanding, and the other end of the spectrum is a bunch of 'AI is your friend' stuff which has almost no mathematical basis but dive straight into using Python libraries and don't give any understanding of the subject itself.
I've looked over Andrew Glassner's book on Deep Learning at No Starch Press and he does a great job providing an overview. What other books / courses are out there that are more wheat than chaff but still mathematically accessible to non-PhD students?
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