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 ...

Learn the essential math behind deep learning in a clear, step-by-step way. From linear algebra to calculus and probability, ...

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 ...

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 ...

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 ...

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 ...

The hype over Large Language Models (LLMs) has reached a fever pitch. But how much of the hype is justified? We can't answer that without some straight talk - and some definitions. Time for a ...