Implementation Stage Of Tanh Activation Function

Tanh help to break non zero centered problem of sigmoid function. Tanh squashes a real- valued number to the range (-1, 1). It’s non-linear too.

Secondary function give us nearly same as sigmoid’s outgrowth function.

It break sigmoid’s debit but it still can’t remove the evaporating grade problem fully.

When we compare tanh activation function with sigmoid, this picture give you clear idea.

# tanh activation function
def tanh(z):
	return (np.exp(z) - np.exp(-z)) / (np.exp(z) + np.exp(-z))# Derivative of Tanh Activation Function
def tanh_prime(z):
	return 1 - np.power(tanh(z), 2)

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