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…igmoid activation function, the Softmax activation function is used for multi-class classification. Softmax function calculates the probabilities distribution of the event over ’n’ different events. In general way of saying, this function will calculate the probabilities of each target class over all possible target classes. Later the calculated probabilities will be helpful for determining the target class for the given inputs.

Conclusion: ReLU and it’s variants should be preferred over sigmoid or tanh activation functions. As well as ReLUs are faster to train. If ReLU is causing neurons to be dead, use Leaky ReLUs or it’s other variants. Sigmoid and tanh suffers from vanishing gradient problem and should not be used in the hidden layers. ReLUs are best for hidden layers. Activation functions which are easily differentiable and easy to train should be used.

Activation functions are functions which take an input signal and convert it to an output signal. Activation functions introduce non-linearity to the networks that is why we call them non-linearities. Neural networks are universal function approximators and …