Function sigmoid

neural_network/two_hidden_layers_neural_network.py:226–236

Applies sigmoid activation function. return normalized values >>> sigmoid(np.array(([1, 0, 2], [1, 0, 0]), dtype=np.float64)) array([[0.73105858, 0.5 , 0.88079708], [0.73105858, 0.5 , 0.5 ]])

(value: np.ndarray)

def sigmoid(value: np.ndarray) -> np.ndarray:
    """
    Applies sigmoid activation function.

    return normalized values

    >>> sigmoid(np.array(([1, 0, 2], [1, 0, 0]), dtype=np.float64))
    array([[0.73105858, 0.5       , 0.88079708],
           [0.73105858, 0.5       , 0.5       ]])
    """
    return 1 / (1 + np.exp(-value))


def sigmoid_derivative(value: np.ndarray) -> np.ndarray: