I would like to buy a book about AI and neural networks written on accessible level for a 17 years old mathematically very gifted student interested in these topics. The book should contain some sections about perceptrons and optical character recognition. I am aware of https://www.deeplearningbook.org/ but it does not fully satisfy me. Mostly, because it goes too slow and too long. For instance, in order to grasp the back-propagation algorithm one needs to read 60 pages! Eqs.(6.49-6.52) are particular shocking, I thought every student should know rules of chain differentiation! We do not write such trivial things in, e.g., theoretical physics.
Now, Internet is full of all possible blogs and tutorials, but it is impossible to filter some nice and concise exposition for people with mathematical background. I notice some popular extremes such as i) prolonged discussion of a single neuron, ii) XOR example, iii) very technical tutorials, which require a lot of python, a lot of packages, web-servers etc.
I am seeking some nice text to create a neural network completely from scratch, and with some impressive performance for e.g. written digits recognition. No reliance on external packages, no object-oriented features, as it may deter young students. But functional programming paradigm is welcome.
Therefore, I was thinking about more refined and concise books, preferably with good typography and illustrations, hard cover, suitable as a gift for a mathematically-inclined student. What would be your recommendation?