Hope the following may help.

"Backpropagation in neural network is a short form for "backward propagation of errors." It is a standard method of training artificial neural networks. This method helps calculate the gradient of a loss function with respect to all the weights in the network"

How to Code a Neural Network with Backpropagation In Python (from scratch)

(https://machinelearningmastery.com/implement-backpropagation-algorithm-scratch-python/)

A Comprehensive Guide to the Backpropagation Algorithm in Neural Networks

(https://neptune.ai/blog/backpropagation-algorithm-in-neural-networks-guide)

How Does Back-Propagation in Artificial Neural Networks Work?

(https://towardsdatascience.com/how-does-back-propagation-in-artificial-neural-networks-work-c7cad873ea7)

Thank you very much. I will go through the links.

when you accept the 5% error, it means that 95% of you are correct