We will implement a variety of algorithms belonging to the Backpropagation family and will visualize their performance using plots. Before jumping into the implementations, let’s understand the ...

The Backpropagation algorithm is a supervised learning method for multilayer feed-forward networks from the field of Artificial Neural Networks. Feed-forward neural networks are inspired by the ...

Training a Neural Network - Uses the processed dataset to build a neural ... to be used for training maximum_iterations – Maximum number of iterations that the algorithm will run. This parameter is ...

Abstract: There are a number of problems associated with training neural networks with backpropagation algorithm. The algorithm scales exponentially with increased complexity of the problem. It is ...

An alternate approach to gradient descent is the exponentiated gradient descent algorithm which minimizes the relative entropy. Exponentiated gradient descent applied to backpropagation is proposed ...

Obtaining the gradient of what's known as the loss function is an essential step to establish the backpropagation algorithm developed ... model of a mechanical neural network.

This paper presents a new neural network structure and namely node-to-node-link neural network (N-N-LNN) and it is trained by real-coded genetic algorithm (RCGA) with average-bound crossover 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 ...