Understand the Maths behind Backpropagation in Neural Networks. In this video, we will derive the equations for the Back Propagation in Neural Networks. In this video, we are using using binary ...

The challenge of speeding up AI systems typically means adding more processing elements and pruning the algorithms, but those approaches aren’t the only path forward. Almost all commercial machine ...

Back-propagation is the most common algorithm used to train neural networks. There are many ways that back-propagation can be implemented. This article presents a code implementation, using C#, which ...

Over the past year or so, among my colleagues, the use of sophisticated machine learning (ML) libraries, such as Microsoft's CNTK and Google's TensorFlow, has increased greatly. Most of the popular ML ...

This deep dive covers the full mathematical derivation of softmax gradients for multi-class classification. #Backpropagation #Softmax #NeuralNetworkMath #MachineLearning #DeepLearning #MLTutorial #AI ...

A new technical paper titled “Hardware implementation of backpropagation using progressive gradient descent for in situ training of multilayer neural networks” was published by researchers at ...

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 way ...

Other neural nets haven’t progressed beyond simple addition and multiplication, but this one calculates integrals and solves differential equations.

Five DECADES of research into artificial neural networks have earned Geoffrey Hinton the moniker of the Godfather of artificial intelligence (AI). Work by his group at the University of Toronto laid ...