TanH [-1 to 1]

Description

The tanh function also takes a real-valued input and squashes it to range between -1 and 1. Unlike the sigmoid function, its output is zero-centered because its range is symmetric around the origin.

However, it has one major drawbacks:

• the vanishing gradients problem (gradients are very small for large positive or negative inputs, which can slow down learning during backpropagation)

Formula