Math to Code is an interactive Python tutorial (all client-side) to teach engineers how to implement math in papers.<p>I was inspired to create it while taking the Fast.ai course and seeing Jeremy Howard share [0] how a "complicated" Frobenius norm equation could be implemented in a single line of Python.<p>Math to Code uses the Skulpt library to interpret Python in JavaScript.<p>It's open source here: <a href="https://github.com/vthommeret/mathtocode" rel="nofollow">https://github.com/vthommeret/mathtocode</a><p>I would appreciate any and all feedback!<p>[0] <a href="https://youtu.be/4u8FxNEDUeg?t=1390" rel="nofollow">https://youtu.be/4u8FxNEDUeg?t=1390</a><p>> <i>It's time to start reading papers. And papers look something like this, which if you're anything like me, that's terrifying. And I'm not going to lie, it's still the case when I start looking at a new paper, every single time, I think, I'm not smart enough to understand this. I just can't get past that immediate reaction. So I just look at this stuff and I go, that's not something I understand.</i>
> <i>But then I remember, this is the Adam paper and you've all seen Adam implemented in one cell of Microsoft Excel.</i>
> <i>1. Even familiar stuff looks complex in a paper!</i>
> <i>2. Papers are important for deep learning beyond the basics, but hard to read.</i>
> <i>3. Learn to pronounce Greek letters.</i>