Backpropagation, short for "backward propagation of errors," is an algorithm that lies at the heart of training neural networks. It enables the network to learn from its mistakes and make ...

In such larger networks, we call the step function units the perceptron units in multi-layer networks. As with individual perceptrons, multi-layer networks can be used for learning tasks. However, the ...

James McCaffrey explains the common neural network training technique known as the back-propagation algorithm.

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Neural networks made from photonic chips can be trained using on-chip backpropagation – the most widely used approach to training neural networks, according to a new study. The findings pave the ...

Back-Propagation is the most common algorithm for training neural networks. Here's how to implement it in C#.

Researchers have developed an algorithm to train an analog neural network just as accurately as a digital one, enabling the development of more efficient alternatives to power-hungry deep learning ...

Modeled on the human brain, neural networks are one of the most common styles of machine learning. Get started with the basic design and concepts of artificial neural networks.