Deep Learning CNN Convolutional Neural Networks with Python - Resnet

The video tutorial introduces Resnet, a type of residual network, and explains its architecture, including the use of residual blocks and identity functions. It highlights the benefits of Resnet, such as reducing training errors and handling vanishing gradients. The tutorial also covers advanced features like batch normalization and 1x1 convolutions. Challenges in training deep networks are discussed, with transfer learning presented as a solution. Transfer learning allows the use of pre-trained models to train deep networks even with limited data.

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