Data Science and Machine Learning (Theory and Projects) A to Z - Classical CNNs: Google Net

The video discusses the architecture of GoogleNet, which uses inception blocks and max pooling to reduce dimensionality. It highlights the challenges faced by deep convolutional neural networks, such as increased training error and vanishing gradients. The video introduces ResNet as a solution to these problems, emphasizing its ability to maintain performance in deeper networks. The transition from inception net to ResNet in Google's systems is also mentioned.

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