If the backpropagation algorithm estimates that increasing a given neuron’s activity will improve the output prediction, for example, then that neuron’s weights will increase. The goal is to change ...

A new technical paper titled “The backpropagation algorithm implemented on spiking neuromorphic hardware” was published by University of Zurich, ETH Zurich, Los Alamos National Laboratory, Royal ...

Training a neural network is the process of finding values for the weights and biases so that, for a set of training data with known input and output values, the computed outputs of the network ...

Backpropagation is not limited to function derivatives. Any algorithm that effectively takes the loss function and applies gradual, positive changes back through the network is valid.

The algorithm, called backpropagation, was the spark that fired up the current revolution of deep learning as the de facto machine learning behemoth. At its core, “backprop” is an extremely effective ...

Backpropagation in CNN is one of the very difficult concept to understand. And I have seen very few people actually producing content on this topic. So here in this video, we will understand ...

Back Propagation is a common method of training artificial neural networks so as to minimize objective function. This paper describes the implementation of back propagation algorithm.