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

The video tutorial introduces ResNet, a type of neural network architecture that uses residual blocks to improve performance and reduce training errors. It explains the architecture and mathematical insights behind ResNet, including the use of identity functions and batch normalization. The tutorial also discusses the challenges of training deep networks and introduces transfer learning as a solution for training with limited data. Transfer learning allows the use of pre-trained models to enhance learning efficiency.

What are the advantages of using deeper convolutional neural networks?

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Discuss the importance of having a large amount of training data for deep learning models.

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Describe the process of transfer learning in the context of deep neural networks.

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