The 2nd edition of Deep Learning with Python[1] (by François Chollet of Keras fame) has a pretty good chapter on the transformer architecture[2]. In fact, the explanations in the book are clear and lucid across the board.

[1]: https://www.amazon.com/Deep-Learning-Python-Francois-Chollet...

[2]: https://en.wikipedia.org/wiki/Transformer_(machine_learning_...

The ones I really enjoyed reading were:

https://www.pyimagesearch.com/deep-learning-computer-vision-...

https://www.machinelearningisfun.com/

and

https://www.amazon.com/Deep-Learning-Python-Francois-Chollet...

Thank you for the tips.

The Deep Learning Book (http://deeplearningbook.org) was one of my main studying materials. How would you compare the other DL book you mentioned (https://www.amazon.com/Deep-Learning-Python-Francois-Chollet...) against this one?

Would you enjoy something that gives a broad overview? Norvig's AI book https://www.amazon.com/Artificial-Intelligence-Modern-Approa... should give you a very broad perspective of the entire field. There will be many course websites with lecture material and lectures to go along with it that you may find useful.

The book website http://aima.cs.berkeley.edu/ has lots of resources.

But it sounds like you are specifically interested in deep learning. A Google researcher wrote a book on deep learning in Python aimed at a general audience - https://www.amazon.com/Deep-Learning-Python-Francois-Chollet... - which might be more directly relevant to your interests.

There's also what I guess you would call "the deep learning book". https://www.amazon.com/Deep-Learning-Adaptive-Computation-Ma...

(People have different preferences for how they like to learn and as you can see I like learning from books.)

(I apologize if you already knew about these things.)