Activation Functions in Artificial Neural Networks

This article assumes a decent understanding of neural networks and backpropagation— for background, check this out.

In all neural networks, the core architecture consists of neurons within several layers; input, hidden, and output. As data is propagated throughout the network, weights adjust their values and help the net make a final prediction of some kind.

An example of a feedforward neural network