Quick, Draw! Kaggle Competition Starter Pack

The code in this repo is all you need to make a first submission to the Quick, Draw! Kaggle Competition. It uses the FastAi library.

I provide instructions on how to run the code below.

This code is based on code from a fast.ai MOOC that will be publicly available in Jan 2019

Making the first submission

You need to have the FastAi library up and running. You can find installation instructions here.
You will also need to download the competition data. The competition can be found under this url. If you do not have a Kaggle account you will need to register. There are many ways to download the data - I use the Kaggle CLI. To set it up you will need to generate an API key - all this information is available in the Kaggle CLI repository. If you do not want to set this up at this point, you can download the data from the competition's data tab.
We will need test_simplified.csv and train_simplified.csv. Please put them in the data directory. If you were to download one of the files using the Kaggle CLI, the command (executed from the root of the repository) would be kaggle competitions download -c quickdraw-doodle-recognition -f test_simplified.csv -p data.
We now need to unzip the downloaded files. cd into the data folder and create a new directory train. Extract the downloaded files by executing unzip train_simplified.zip -d trains_csvs.
Let's prepare our data now. Start the jupyter notebook server and open data_preparation.ipynb and run all.
Now that we have the data, let's train. Open first_submission.ipynb. If you have kaggle CLI installed and configured, you can uncomment the last line and hit run all. See you on the leaderboards :)