Time to Revisit Tangle?

Engaged, as ever, in displacement activity, I just came across Distill (via https://deepmind.com/blog/distill-communicating-science-machine-learning/), yet another “modern medium for presenting research”, this time “in the area of Machine Learning”.

The most recent (April, 2017) paper, Why Momentum Really Works, includes several inline embedded interactive that let you explore some of the maths described in the paper.

Another of the interactive features allows you to play with the parameters of an equation and see the result:

This interaction reminded me of Bret Victor’s Tangle.js library, which is quite old now (I’m not sure if it is/ever needs to be maintained?).

Poking around in the Distill post, I couldn’t trivially see how to create my own versions of the above tangle-like interaction, which made me think that when publishing docs like that it would be really handy if folk also documented some simple, minimal how to’s on how the interactives were created.

I was also prompted to have a quick poke around to see whether tangle like features are supports in Jupyter notebooks or Rmd/knitr/shiny. It seems that there are some old demos of using tangle in those environments – bollwyvl/ipytangle and hadley/tanglekit – but I haven’t had a chance to try them to see if they still work…

PS In passing, I note that the RSTudio folk have just produced a toolkit for generating tutorials from RMarkdown docs – Introducing learnr. Lowering the boundaries to educators creating their own interactives – again. Just a shame so few want to try out such things and explore how we might be able to make use of them… :-(

Animated GIFs created using: Giphy Capture: