Welcome to the community, @RohitKamalV!
In addition to @pastorsoto’s great answer:
It describes the exponent e.g. used in a logistic regression task; or let’s say:
- x: the input of a sigmoid function,
- b: the bias
- w: the weight(s)
where w and b are the model parameters that are learned within model training.
But dependent on your model you can also interpret this term as the cell body of a neuron within a larger neuron network (e.g. at a output layer of a binary classification problem):
Here also a visual interpretation possibility with a neuron where you can think of f as a sigmoid function, representing a nonlinear activation function of this layer:
Source: Choice of activation function - #8 by Christian_Simonis
Best regards
Christian