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

There are two different techniques for training a neural network: batch and online. Understanding their similarities and differences is important in order to be able to create accurate prediction ...

We’re going to talk about backpropagation. We’re going to talk about how neurons in a neural network learn by getting their math adjusted, called backpropagation, and how we can optimize ...

The standard “back-propagation” training technique for deep neural networks requires matrix multiplication, an ideal workload for GPUs. With SLIDE, Shrivastava, Chen and Medini turned neural network ...

Neural-network training is computationally demanding, to extremes, and when training a model from scratch, a developer can expect training times of up to five days on a high-end multi-GPU machine.

A new type of neural network made with memristors can dramatically improve the efficiency of teaching machines to think like humans. The network, called a reservoir computing system, could predict ...

Training a traditional neural network on the same data set produced a vowel-recognition accuracy of just over 90 percent. For the optical neural network, accuracy was just over 75 percent.