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Level 4 challenge: Kaggle competition: Dogs vs. Cats

The task of this challenge is simple to describe, make a submission to Kaggle for the famous Dogs vs. Cats competition!

Here is a little bit extra requirements:

  1. You MUST use Jupyter Notebook.

  2. Not mandatory, but strongly recommend to use PyTorch.

  3. In your notebook, include the public score of your submission to kaggle.

  4. If your classifier is not 100% accurate, provide an analysis on the incorrectly classified inputs.

Bonus

Take a harder challenge on Kaggle, Google Landmark Recognition Challenge. This dataset is huge, and it will take a long time to download, one of the participant is kind enough to provide an one-stop download of all the images in smaller size, see this discussion thread.

Besides training a high performance classifier, try to use visualization to understand which part of the image is the most salient to the classification decision (You may take a look into CAM: Class Activation Mapping).

Remarks:

  1. If the data is no longer available at the time being, you may look for another Kaggle competition that interests you, build a model and try to visualize.

  2. If you take this bonus part, the easy Dogs vs. Cats challenge can be skipped, but the above requirements are still applied.

  3. A well done bonus part can outweigh everything else!