deep-learning-intro
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Using prefilled notebooks
I taught this lesson last week (third time!) at the University of Wisconsin-Madison. This year, I experimented with using prefilled Jupyter notebooks rather than having everyone type out all of the code from scratch. I tried the same approach at a recent Intro to Text Analysis workshop, and learners seemed to really appreciate that we could spend more time unpacking concepts and less time fiddling with typos. I think I would generally argue in favor of using prefilled notebooks at any workshop that (a) requires more time unpacking concepts / intended for intermediates and (b) assumes learners already have background programming experience. That said, additional exercises may be warranted when using too much prefilled code (mainly to get additional practice using the Keras syntax).
Using prefilled notebooks, we were able to effectively teach episodes 1-4 (getting through advanced layers) in a 3 half-day schedule (8:30am-12:30pm on each day; 10 min. breaks every hour). We got about halfway through the transfer learning episode before we had to cut things off. I will most likely try a 4 half-day schedule next year.
If others are on board with using prefilled notebooks or want to give it a shot, here is a link to a Jupyter notebook you can use to convert each episode's R markdown file to a Jupyter notebook (allowing us to quickly generate prefilled scripts when lesson materials evolve). I'm happy to upload this notebook to the repo if the maintainers/authors are in support of this. I'm not expecting everyone to agree with the use of prefilled notebooks, but I think it's worthwhile to give other instructors the option. I'll warn folks that the conversion isn't 100% perfect. Code output that is shown on the lesson page is shown in the converted notebooks, and those cells have to be deleted manually.