Lec5
Training Neural Networks II: Weight Initialization(Activation Statistics, Xavier Initialization, Kaiming / MSRA Initialization, Residual Networks…), Overfits, Regularization, Regularization, Data Augmentation
Training networks
Lec2
Introduction of Neural Networks I,Deep Neural Networks, Activation Fuctions
Neural networks
Lec3
Introduction of Neural Networks II,Universal Approximation, Convex Fuctions.
1 Video & PDF
https://cs231n.stanford.edu/slides/2017/cs231n_2017_lecture9.pdf
This lecture delves into the application of deep learning models, such as convolutional neural networks (CNNs), for various computer vision tasks.
Deep LearningCNNsComputer Vision
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