Lab03

Lab 3

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Homework 3: Homework3.pdf

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For self-study (all students):

• Tensorboard: https://pytorch.org/docs/stable/tensorboard.html
• Weights and Biases: https://docs.wandb.ai/guides/integrations/pytorch
• AlexNet:
  • https://www.cs.toronto.edu/~hinton/absps/imagenet.pdf
  • [Classic] ImageNet Classification with Deep Convolutional Neural Networks
• ResNet:
  • https://arxiv.org/abs/1512.03385
  • [Classic] Deep Residual Learning for Image Recognition
• PyTorch image models
  • https://huggingface.co/docs/timm/index
  • https://huggingface.co/models?library=timm&sort=trending

Advanced (for students who want to learn more):

• TODO

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• Berkeley Deep Learning::
  • Neural Network Optimization (Backprop review, Adam, BatchNorm, Dropout, Skip connections)
  • Advanced CV Architectures (AlexNet + ResNet)
• Interactive Visualization of Optimization Algorithms in Deep Learning