# Activation Function

In a neural network, an activation function normalizes the input and produces an output which is then passed forward into the subsequent layer. Activation functions add non-linearity to the output which enables neural networks to solve non-linear problems. In other words, a neural network without an activation function is essentially just a linear regression model.

Common activation functions include

**Linear**,**Sigmoid**,**Tanh**, and**ReLU**but there are many others.Last modified 4yr ago