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{{def|Neural network||n|}}An artificial neural network is a computing system vaguely inspired by the biological neural networks that constitute animal brains.
{{def|Neural network||n|}}An artificial neural network is a computing system vaguely inspired by the biological neural networks that constitute animal brains. “Vaguely inspired” in the way that ''Conan the Barbarian'' was inspired by [[Nietzsche]].


It is based on collections of nodes called artificial neurons, which loosely model the neurons in a biological brain. Each connection can transmit a signal to other neurons which then processes it and can signal neurons connected to it. The “signal” at a connection is a real number, and the output of each neuron is computed by some non-linear function of the sum of its inputs. The connections are called “edges”. Neurons and edges typically have a weight that adjusts as learning proceeds.
It is based on collections of nodes called “artificial neurons”, which loosely model the neurons in a biological brain. It is very good at crunching terabytes of data to recognise dogs on the internet, and predict that, when you want to reply to a colleague’s [[LinkedIn]] [[humblebraggadocio]], “So inspired by you!” is what you really want to say.

Revision as of 11:52, 14 December 2020

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Neural network (n.)
An artificial neural network is a computing system vaguely inspired by the biological neural networks that constitute animal brains. “Vaguely inspired” in the way that Conan the Barbarian was inspired by Nietzsche.

It is based on collections of nodes called “artificial neurons”, which loosely model the neurons in a biological brain. It is very good at crunching terabytes of data to recognise dogs on the internet, and predict that, when you want to reply to a colleague’s LinkedIn humblebraggadocio, “So inspired by you!” is what you really want to say.