Hard disagree, to the point where I'm not sure there's not some confusion at play here. I find using indices and summations generally confusing and hard to rea

Hard disagree, to the point where I'm not sure there's not some confusion at play here. I find using indices and summations generally confusing and hard to read/follow/understand. To me, it's so much simpler to draw out the computational graph, derive the gradient with a single element (so I'm in agreement with you guys here?), see how that applies the same to every element the same, then scale up to the vectorized/matrix version. > and you need to memorize a bunch of new rules to apply it There's nothing to memorize though..? Is there something called "matrix calculus" that's different than just drawing the computational graph and deriving the gradient in the way I described..? Like, is this "matrix calculus"? - https://cs231n.github.io/optimization-2/ https://cs231n.github.io/optimization-2/ If so, what is there to memorize here?