I'm really happy that GitHub supports rendering ipynb files so nicely. Makes it easy to glance at repos like this without cloning and firing up a Jupyter notebook.
It seems like the algorithms aren't that complex, after all they have to be completed in one day. There might be more value in something like, 12 algorithms/side projects a year. Enough time is had in a month to actually develop something meaningful, not necessarily an entire side project but a deep understanding of a specific algorithm.
I think the hard part of these algorithms was discovering them. If you know what you're making at some point it just boils down to how quickly you can type. Took Einstein forever to discover E=mc^2 but I can type the full equation out in no time.
That's what I mean, in that most if not all of these algorithms don't seem to be discovered novelly, but more that they are universally known now, and indeed it seems like the author typed them out and called it a day, literally. I'm saying that there is more pedagogical value in meditating and creating from scratch, algorithms for some purpose over the span of a month, rather than reading about known algorithms and typing them out. If these same algorithms were indeed realized from scratch by the author with no prior knowledge , then I commend them, but still, doing so in only a day each seems highly unlikely.
I often find that when I try something in practice I become aware misunderstandings i have, and details that I might have missed. Of course, if you implement enough algorithms you will learn which mistakes you commonly make and start making fewer of them.
