Numbers recognition

Hi !
I've tried to implement the same neural network library as in the videos
However I have some problems

I am coding in Python, in Processing. Just to warn you, I am not really familiar with Python and Processing, that's why i have everything in one file ( I wasn't able to separate it in defferent files and then import them , if you know how to do it please tell me)

So the problem i am getting, is that the neural network is getting stuck. In fact I rarely go over 85% accuracy with is quite bad I think. And it doesn't matter how long i let it run, arround 85% , the accuracy just randomly changes. I know that my code is not really clear and messy , but could someone try to find what's going on ? Just so you know, I've stored, all the images in 60 000 files (1 per image ) , each containing a number between 0 and 1 for the pixel color

I've also added the possibility to have several hidden layers in the neural network
However, iam not sure if I am doing the backpropagation and the gradient descent correctly, could anyone check and tell me ?

Thanks a lot, I am new to GitHub so sorry if I did things wrong
( and by the way, I am French, that's why my english might be bad )

Review the single-file Python/Processing implementation referenced in the issue and reproduce the reported training behavior, starting with the backpropagation and gradient-descent paths. No file or test is named; done means identifying the cause of the accuracy plateau and demonstrating the corrected training behavior or a clear explanation of the limitation.

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