Initialise the model parameters

Instructions

• Make sure the parameters’ sizes are right. Refer to the doc above.

• we need to initialize the weights matrices with random values.

  • Use: np.random.randn(a,b) * 0.01 to randomly initialize a matrix of shape (a,b).

• You will initialize the bias vectors as zeros.

  • Use: np.zeros((a,b)) to initialize a matrix of shape (a,b) with zeros.

def initialize_parameters(n_x, n_h, n_y):
    """
    Argument:
    n_x -- size of the input layer
    n_h -- size of the hidden layer
    n_y -- size of the output layer
    Returns:
    params -- python dictionary containing your parameters:
    W1 -- weight matrix of shape (n_h, n_x)
    b1 -- bias vector of shape (n_h, 1)
    W2 -- weight matrix of shape (n_y, n_h)
    b2 -- bias vector of shape (n_y, 1)
    """

    return parameters

Expected Output

W1, b1, W2, b2 –> some values