Ultra simplified "MNIST" in 60 lines of Python with NumPy

That reminds me of the article „a neural network in 11 lines of code“ from 2015 (although not on MNIST, rather some kind of XOR)

https://iamtrask.github.io/2015/07/12/basic-python-network/

Beautiful! Same in spirit as what I was going for, but even better. I really like the way the weights are updated in this one. Thanks for showing me this!

Tinygrad offers a superior MNIST implementation with minimal dependencies[0].

[0] https://github.com/tinygrad/tinygrad/blob/master/docs/mnist....

Autograd hides the backward pass in that implementation, but this code spells it out explicitly.

The description: "no dependencies."

The first line: "import numpy as np"

you got me, lol. to be fair the only reason numpy is there is because truly pure python doesn't have matmuls, and I didn't think reimplementing it wouldn't serve a didactic purpose.

A cool idea for a v2 without numpy would be implementing matmuls with lists, matrix transpose with zip() and switching np.exp for math.exp. And getting all that on fewer lines as possible.