optimization 썸네일형 리스트형 07. Training Neural Networks(2) CNN Preivew Lecture 7 continues our discussion of practical issues for training neural networks. We discuss different update rules commonly used to optimize neural networks during training, as well as different strategies for regularizing large neural networks including dropout. We also discuss transfer learning and finetuning. Keywords: Optimization, momentum, Nesterov momentum, AdaGrad, RMSPro.. 더보기 03. Loss Functions and Optimization Lecture 3 continues our discussion of linear classifiers. We introduce the idea of a loss function to quantify our unhappiness with a model’s predictions, and discuss two commonly used loss functions for image classification: the multiclass SVM loss and the multinomial logistic regression loss. We introduce the idea of regularization as a mechanism to fight overfitting, with weight decay as a co.. 더보기 이전 1 다음