This python program implements the backpropagation algorithm for Neural Networks. There are two steps: Pre-processing the dataset. The two arguments for the program: input path of the raw dataset; ...

The success of many neural networks depends on the backpropagation algorithms using which they have been trained. The backpropagation algorithm computes the gradient of the loss function with respect ...

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 (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.

Load forecasting plays a significant role in planning and operation of electrical power networks. Artificial neural networks have been extensively employed for load forecasting over the last 20 years, ...

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.