def run_linear_regression(data_x, data_y):
    iterations = 100000
    alpha = 0.0001550

    no_features = data_x.shape[1]
    len_data = data_x.shape[0] - 1

    theta = np.zeros((1, no_features))

    for i in range(0, iterations):
        theta = run_steep_gradient_descent(data_x, data_y, len_data, alpha, theta)
        error = sum_of_square_error(data_x, data_y, len_data, theta)
        print(f"At Iteration {i + 1} - Error is {error:.5f}")

    return theta