Lesson 5

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This week's links

  • The notebooks:
    • Lesson 5 shows the IMDB sentiment analysis
    • Word vectors contains the visualization of glove vectors
    • char-rnn is the RNN "Nietzsche generator" - we only briefly looked at this; we'll be discussing this notebook more next week
    • Imagenet batchnorm is the method used to add batchnorm to imagenet. This is optional - now that we've done this for you, it's included in vgg16bn.py; we're providing the notebook for those of you that are interesting in learning how we did it
  • The python scripts:
    • The VGG network with batchnorm - we will use this now instead of vgg16.py and automatically downloads the new weights when first used
    • utils.py - For finetuning, we will start using vgg_ft_bn (which uses VGG with batch norm) instead of vgg_ft
  • The datasets:
    • The IMDB dataset is part of keras, and download code is part of the lesson 5 notebook.

Information about this week's topics


  • Try to make sure you've completed the key goals from previous weeks - top 50% of kaggle result on each of:
    • dogs and cats redux
    • state farm
  • if you've already done that, try to either: