The Mathematical Engineering of Deep Learning

The different lessons seem to use different programming languages for their examples. I see R, Julia, and Python.

Which is cool. But it's not very well explained. One chapter just introduces R code, without even saying that's the language.

So some explanation about which language is being used when, and if there is a reason for choosing one over the other, would be useful.

What would be great is make the code windows tabbed where each code block is listed in R, Python, and Julia... something similar to Dive into Deep Learning. For example: https://d2l.ai/chapter_linear-networks/linear-regression-scr....

To the book author, thank you so much for all of the hard work on this. I bookmarked it and will refer to it in the future.

I know that it’s not related to the course’s content but: I never liked the “deep learning is the new electricity”. It sounds dumb.

I am unfamiliar with the term mathematical engineering. What does it even mean?

It means there's no good theory yet, just some tricks that seem to work.