I am a newbie at deep learning. I came so watching many tutorials, reading some articles on implementing neural networks with hidden layers. But all the tutorials seem to TensorFlow, Pytorch, or something else. I have a concept of SGD,MB SGD, chain rule, linear algebra. I know how to calculate the gradients for the hidden layer and how to update the weights. But I could not be able to implement it in my own code.
Anjal Binayak Adhikari
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How to implement backpropagation from scratch in python without any libraries?
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Top comments (3)
I would recommend reading this book:
Tariq Rashid
Make Your Own Neural Network
Mainly about implementation of a neural network without library's expect numpy. Really good book
It's really good in explaining it, also all the code is on GitHub if you just want the solutions.
I got a lot of recommendations for this book. I gotta buy it now :)
did you get to implement the backpropagation using simple python?