{"version":"1.0","type":"rich","provider_name":"gaks.ai AI Glossary","provider_url":"https://gaks.ai/glossary","title":"Activation Function — AI Glossary","author_name":"Glenn Katrud Solheim","author_url":"https://gaks.ai","width":600,"height":200,"html":"

AI Glossary — gaks.ai

Activation Function

A mathematical function applied to the output of a neuron in a neural network, determining whether and how strongly that neuron fires. In practice, a neural network passes data through repeated cycles of linear transformation followed by an activation function, and it is this alternation that gives the network its ability to learn complex, non-linear patterns. Without activation functions, stacking layers would be mathematically pointless, as any number of linear transformations collapse into a single one.

Source: gaks.ai/glossary/activation-function →
"}