Activation Functions
The activation function defines the output of a neuron in terms of the induced local field. Activation functions are a single line of code that gives the neural nets non-linearity and expressiveness.
There are many activation functions. Some of them are as follows:
Identity function
The identity function is a function that maps input to the same output value. It is a linear operator in vector space. Also, a known straight-line function where activation is proportional to the input. The simplest example of a linear activation function is a linear equation.
f(x) = a * x,where a ∈ R
The major problem with such kind of linear function it cannot handle complex scenarios.
Binary Step Function
In Binary Step Function, if the value of Y is above a certain value known as the threshold, the output is True(or activated) and if it’s less than the threshold then the output is false (or not activated). It is…
