Artificial Intelligence, Artificial Neural Network, Computer Science, Linear Regression, Python.
np.mean((y_prime - y)) def train(self, x, y, verbose=False, epochs=10): best_loss = -1 best_theta = 0 best_beta = 0 losses = [] accuracies = [] for ephoc in range(epochs): y_prime = self.predict(x) self.theta -= self.learning_rate * self.derivate_params(y, y_prime, x) #Adjust parameters based on