Ans: Sigmoid is an activation function which is in S shape curve. It takes real value as an input and gives the output which is in between 0 and 1. It is non-linear in nature; it is continuously differentiable and has fixed output range of values. It gives a continuous form of output unlike Step function. It has smooth gradient. At the ends of the sigmoid function, Y values change less with change in X values, due to which vanishing gradient arises which results in Network refuses to learn further or too slow to make correct Predictions. Sigmoid Function is not zero centered.
Explain Logistic or Sigmoid Activation Function
