Activation Functions in Neural Networks [12 Types & Use Cases]

An Activation Function decides whether a neuron should be activated or not. This means that it will decide whether the neuron's input to the network is important or not in the process of prediction using simpler mathematical operations. The role of the Activation Function is to derive output from a set of input values fed to a node (or a layer). Let's take a step back and clarify: What exactly is a node? Well, if we compare the neural network to our brain, a node is a replica of a neuron that receives a set of input signals--external stimuli. Depending on the nature and intensity of these input signals, the brain processes them and decides whether the neuron should be activated ("fired") or not.