Maybe interesting, I used it for a toy implementation of the GPT architecture[1] in about 500 lines.

(I studied with one of the authors, Dr. Daniel Friedman; wasn't super involved here but proofread a late draft and TA'd for a course based off the book.)

[0]: https://github.com/themetaschemer/malt

[1]: https://github.com/sporkl/malt-transformer

The Little Learner: A Straight Line to Deep Learning - https://news.ycombinator.com/item?id=34810332 - Feb 2023 (96 comments)

"Pub date: February 21, 2023"

I studied pure math in college, and we were required to take 2 "Computer Science" classes as part of that program. Mainly memorizing textbook algorithms and data structure implementations in Java. I hated programming for years after that, until during graduate school I came up with a project of my own that organically required knowledge of Matlab and later Python. I loved programming after that.

I hope books like this can help new students avoid the trough of disillusionment that can sometimes happen if you're forced to learn a cool subject (like programming) in a very uncool way.

Personally, I would not recommend this book to a young person interested in deep learning and programming (based on the table of contents). I would probably recommend they first learn calculus and use Python to make plots while doing so. Then read Fleuret's "The Little Book of Deep Learning" and try to implement simple models in PyTorch.