Activation function: Difference between revisions

==Introduction==

An [[activation function]] in [[machine learning]] is a mathematical function applied to the [[output]] of a [[neuron]] in a [[neural network]]. This determines what happens next based on [[input]] to the neuron and is an essential element of its [[architecture]]. The activation function enables neural networks to learn [[nonlinear]] (complex) relationships between [[features]] and the [[label]].

==Explore Like I'm 5 (ELI5)==

Activation functions are like special glasses that help computers see better. They alter pictures, sounds, or other items by altering their hue or brightness; this makes it easier for the computer to differentiate what the picture or sound is and how best to process it. Different glasses are used for various tasks like seeing colors or finding loudest noise.