Classifies an image as containing either a dog or a cat (using Kaggle's public dataset), but could easily be extended to other image classification problems.

• PyTorch / Torchvision
• Numpy
• PIL
• CUDA

The data directory structure I used was:

• project
  • data
    • train
      • dogs
      • cats
    • validation
      • dogs
      • cats
    • test
      • test

The result of the notebook in this repo produced a log loss score on Kaggle's hidden dataset of 0.04988 -- further gains can probably be achieved by creating an ensemble of classifiers using this approach.