Both of sigmoid function or perceptron decision function (step function) are differentiable.1 pointTrueFalse

Which of the following statements about the sigmoid function is NOT true? The derivative of the sigmoid function can be negative. The sigmoid function is continuous and differentiable. The sigmoid function maps any input value to a value between 0 and 1. The sigmoid function can be used as an activation function in neural networks.

What is the problem with the tanh and sigmoid activation function?1 pointThey are discontinuous functionsYou can't take the derivativeThe derivative is near zero in many regionsThey are periodic functions

Which of the following functions is differentiable?1 pointSigmoid, tanh, ReLuSigmoid, Log likelihood, ReLuLog likelihood, ReLu, tanhLog likelihood, Sigmoid, tanh

True or False? If the derivative of all the sigmoid functions are approximately zero, therefore, when we apply the update equation for gradient decent, nothing will happen.1 pointFalse True

The cut off value for the sigmoid function as discussed is :