Find out why backpropagation and gradient descent are key to prediction in machine learning, then get started with training a simple neural network using gradient descent and Java code.

Neural networks are computing systems designed to mimic both the structure and function of the human brain. Caltech ...

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 ...

The artificial neural network (ANN) theory and method was adopted to establish a back propagation (BP) neural network model for the assessment of water quality. Considering the water quality in the ...

For our purposes, the key point is that backpropagation radically expanded the scope of trainable neural networks. People were no longer limited to simple networks with one or two layers.

Reverse neural networks have also been used to create realistic audio and music. One example is the development of WaveNet, a generative neural network that is capable of producing high-quality audio ...

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.