Hands-On Mathematics for Deep Learning

Sigmoid

To start, we will take a look at sigmoid since we've already encountered it. The sigmoid function is written as follows:

The function looks as follows:

The sigmoid activation function takes the sum of the weighted inputs and bias as input and compresses the value into the (0, 1) range.

Its derivative is as follows:

The derivative will look as follows:

This activation function is usually used in the output layer for predicting a probability-based ...