> For the complete documentation index, see [llms.txt](https://machine-learning.paperspace.com/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://machine-learning.paperspace.com/wiki/activation-function.md).

# 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](/wiki/linear-regression.md) model. 

### Activation Function Types

Common activation functions include **Linear**, **Sigmoid**, **Tanh**, and **ReLU** but there are many others.

![](/files/-LvO3qs2RImYjpBE8vln)