In neural networks, an activation function defines the output of a neuron.

The activation function takes the dot product of the input to the neuron (\(\mathbf x\)) and the weights (\(\mathbf w\)).

Typically activation functions are nonlinear, as that allows the network to approximate a wider variety of functions.