def initialize_parameters_deep(layer_dims):
    
    np.random.seed(3)
    parameters = {} # we will put initialized values in the dictionary
    L = len(layer_dims)            # number of layers in the network

    # we need a for loop to iterate through the layers and initialze the parameters W and b for every layer
    for l in range(1, L):
        parameters['W' + str(l)] = np.random.randn(layer_dims[l], layer_dims[l-1]) * 0.01
        parameters['b' + str(l)] = np.zeros((layer_dims[l], 1))

        
    return parameters