I might be helping author a textbook based on our upcoming introduction to machine learning MOOC. Which maybe one day would lead to a deep learning book - but that would be years away!

(BTW, I used to think I didn't like videos for learning, but actually I now think some material works best in this format. E.g. in this case we're walking through interactive notebooks, and you can follow along too. Some of the material is animated, and often I'm building up drawings as I talk. Maybe it won't be for you, but it might be worth giving it a go to see...)

Just another thought on this, as someone slowly trying to work his way through part 1 (and generally very happy with it, thanks for this amazing resource!): videos are great when they're really short. It's tough for working people to find enough unbroken time to watch an hour or two long video, like the ones in fast.ai (as amazing as they are), especially with frequent pauses for note-taking and such.

But it's much easier to handle smaller chunks. This is probably my only critique of/gripe about fast.ai---the videos pack a lot of topics in, and they could be broken at topic boundaries to make them easier to use.

Thanks for the feedback! One thing you may be interested in, if you haven't seen it, is that you can right-click the video and copy a link to the current time code, so you can always go back to where you were (or just pause the video in a tab and return later).

Personally, I really hate the Coursera approach of lots of separate short videos - I totally get that some people like it, and that's fine, but it's not something I want to do myself.

Oh, I did not know you could link to specific time slices! That's a big help, thanks!

another thing I used a ton when going through part 1 was being signed into my google account, google kept track of my progress through the video and if I exited out and came back on a different machine it would resume where I last left off, then I would back up a few minutes to build that context back up (or attempt to anyways).

I'm traditionally a textbook person too, but I really like fast.ai. You get to see how to tinker with things in real time (which is often clunky in a textbook), and there's a lot of informal folklore that people don't normally write in academic textbooks. If you're dead set against video you could just work through the notebooks yourself and read the referenced papers on the website.

I have the same problem. Too traumatized (when I was young) by a person teaching in a lecture format. I like self discovery and tinkering.