Sgd, Machine Learning, Stochastic Gradient.
[self.log_loss(self.x_cv, self.y_cv)] def evaluate_the_model(self, epoch): self.tr_log_loss_lst.append(self.log_loss(self.x_tr, self.y_tr)) self.cv_log_loss_lst.append(self.log_loss(self.x_cv, self.y_cv)) print(f"---> Epoch {epoch}") print(f"Tr ave loss {self.tr_log_loss_lst[-1]} & CV ave loss