bookish

:) Yeah, I use my own internal markdown to generate really nice html (with fast latex-derived images for equations) and then full-on latex. (tool is https://github.com/parrt/bookish) I prefer reading on the web unless I'm offline. The latex its super handy for printing a nice document.

Terence Parr's 'bookish' is worth a look too, for those wanting to stick to markdown + embedded LaTeX https://github.com/parrt/bookish

(In addition / As an alternative) to Pandoc, has anyone tried Bookish [0] by Terrence Parr of ANTLR fame? It was referenced by Jeremy Howard in a HN comment [1] on the submission for their "Matrix Calculus for Deep Learning " HN submission of 18 days ago [2]: >Jeremy here. Here to answer any questions or comments that you have. > >But more importantly - I need to mention that Terence Parr did nearly all the work on this. He shared my passion for making something that anyone could read on any device to such an extent that he ended up creating a new tool for generating fast, mobile-friendly math-heavy texts: https://github.com/parrt/bookish . (We tried Katex, Mathjax, and pretty much everything else but nothing rendered everything properly). > >I've never found anything that introduces the necessary matrix calculus for deep learning clearly

Jeremy here. Here to answer any questions or comments that you have. But more importantly - I need to mention that Terence Parr did nearly all the work on this. He shared my passion for making something that anyone could read on any device to such an extent that he ended up creating a new tool for generating fast, mobile-friendly math-heavy texts: https://github.com/parrt/bookish . (We tried Katex, Mathjax, and pretty much everything else but nothing rendered everything properly). I've never found anything that introduces the necessary matrix calculus for deep learning clearly, correctly, and accessibly - so I'm happy that this now exists.