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Sigmoid Derivative

Functions

sigmoid_derivative(Z)

Compute the derivative of the sigmoid activation function.

Parameters:

Name Type Description Default
Z ndarray

The input array.

 required

Returns:

Type Description

numpy.ndarray: An array with the same shape as Z, containing the sigmoid derivative values.
Example 
Z = np.array([[-1, 0], [1, 2]])
dZ = sigmoid_derivative(Z)
print(dZ)
Source code in microkeras/activations/sigmoid_derivative.py 
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def sigmoid_derivative(Z):
    """
    Compute the derivative of the sigmoid activation function.

    Args:
        Z (numpy.ndarray): The input array.

    Returns:
        numpy.ndarray: An array with the same shape as Z, containing the sigmoid derivative values.

    Example:
        ```python
        Z = np.array([[-1, 0], [1, 2]])
        dZ = sigmoid_derivative(Z)
        print(dZ)
        ```
    """
    activation = sigmoid(Z)
    return activation * (1 - activation)