Neural Network
Neural Network
A system inspired by the neural circuits of the human brain, designed to enable computers to learn and make decisions.
In Simple Terms
A neural network is a system that lets computers learn from experience—just like humans—and recognize complex patterns. It powers technologies such as automatically telling apart a cat from a dog in a photo, or converting spoken words into written text. The more data it receives, the better the computer gets at identifying key features and arriving at the right answers.
Behind the Name
In "Neural Network," "neural" means "relating to nerves," and "network" means "an interconnected system or web." The name reflects the way neurons in the human brain connect and relay information to one another—the very inspiration behind this system.
Take a Closer Look!
A neural network is a mathematical model inspired by the workings of the brain, built to learn features and patterns from data.
It was developed to let computers take in large amounts of data and discover the underlying rules on their own.
Roughly speaking, the system is made up of three layers stacked together: an input layer, a hidden layer, and an output layer.
When shown an image, for instance, it first reads color and edge information, then consolidates shape features, and finally outputs what the image represents.
Deep learning—which has achieved remarkable results—is essentially this same neural network stacked many layers deep.
This depth makes it possible to analyze complex images and generate natural-sounding text, much like a human would.
From facial recognition on smartphones to automatic translation, this technology is quietly at work throughout everyday life.