What papers or textbooks do i need to read to have all the basics / background knowledge to use pytorch and understand what I am doing based on solely the documentation pytorch provides?

  • howrar@lemmy.ca
    3·
    7 months ago

    I know you said you couldn’t find what you were looking for in the docs, but just in case you were looking in the wrong place:

    • Conv2d gives you the exact mathematical formula that’s implemented along with some examples.
    • ReLU does the same and is even simpler.

    Besides the convolution operator, I believe all the math should have been covered in high school (summation, max, and basic arithmetics). And convolution is also just defined in terms of these same operations, so you should be able to understand the definition (See the discrete definition in the wiki page under the “cross corrosion of deterministic signals” section).

    The math does look daunting if it’s your first time encountering them (I’ve been there), and sometimes all you really need to confirmation that you already have all the requisite knowledge.

    • AnarchistsForDemocracy@lemmy.worldOP
      1·
      7 months ago

      thank you yeah, I found the conv2d and reLu on pytorch’s home page i am struggling with the arguments that conv2d accepts and i just realized i need to refresh linear algebra first.

      Learning about hermitians and transposed and inverted matrices, tbh i remembered how to multiply and about the determinant and all that but there is a lot that i forgot. So i am digging through the matrix cookbook currently also reading a book on deep learning in parallel.

      I am trying to find a way to get a hold and read this paper: Krizhevsky, A., Sutskever, I. & Hinton, G. ImageNet classification with deep convolutional neural networks. In Proc. Advances in Neural Information Processing Systems 25 1090-1098 (2012)

      but have failed so far…