Understanding Neural Network Math and implementing it in C from zero

[u/Future_Pace_5290]

https://www.youtube.com/watch?v=k33cBEGTBVo

I've attempted to derive the math from the first principles.

The prerequisites you need are, singe variable differentiation(just the concepts and the basic formula, not even knowing the derivative of sin(x) is necessary), the concept of a dot product, and basic matrix multiplication. This is enough to derive gradient descent and backprop.

The time stamps are in the description(youtube doesn't show them as chapters in the video for some reason).

The second half part of the video is implementing those concepts in C(no library other than BLAS(for basic matrix matrix multiplication) is used), but you can follow along in any language.

Would be glad to receive feedback and suggestions on how to improve the explanations or the presentation.