In this post I will discuss the backpropagation algorithm in Different neural networks which are : MLP; CNN; RNN; LSTM For all these networks, this post will be focused on Backpropagation only. I will ...

The backpropagation algorithm computes the gradient of the loss function with respect to the weights. these algorithms are complex and visualizing backpropagation algorithms can help us in ...

This repository contains the implementation of the backpropagation algorithm to train a neural network from scratch. The implementation supports networks with an adjustable number of layers and ...

Let’s understand this backpropagation through a neural architecture. The above network contains an input layer with two feature neurons and a bias neuron, a hidden layer with two hidden neurons, and a ...

Backpropagation in neural Network is vital for applications like image recognition, language processing and more. Neural networks have shown significant advance. About Us; ... The second backward ...

The backpropagation (BP) algorithm is a one of the most common algorithms used in the training of neural networks. The single offspring technique (SOFT algorithm) is a new technique (see Likartsis, A.

Accuracy obtained with exponentiated gradient descent back propagation was comparable to the gradient descent back propagation while convergence was faster. The results show that exponentiated ...

Turing Award winner and deep learning pioneer Geoffrey Hinton, one of the original proponents of backpropagation, has argued in recent years that backpropagation does not explain how the brain works.