Data Science, Linear Regression, Machine Learning, Python, Numpy.
1) containing the true values of y. yhat: A numpy array of shape (m, 1) containing the predicted values of y. Returns: betas: A numpy array of shape (1, n+1) containing the updated values of the betas. """ dLdb = 2 * np.dot((yhat - y).T, X) / self.m betas = betas - self.learning_rate * dLdb return