This page lists some useful resources which you can use for the challenge.

Reproducible Code

Code submission are mandatory for all submitted reports. We recommend that you:

  • Publish your code in a repository (e.g. on GitHub, GitLab, BitBucket) and anonymize it according to our double blind guidelines.
  • Document your code appropriately
  • Have a README.md file which describes the exact steps to run your code. You can refer to the ML Code Completeness Checklist to write the README file and make sure your code submission is complete.
  • See this blog post on best practices for reproducibility.

Compute Resources

  • Google Colaboratory provides free GPU backed Jupyter Notebooks
  • Code Ocean provides 10hrs/month of GPU accelerated platform free to academics. Code Ocean is a cloud-based research collaboration platform.
  • Instructors can apply for Google Cloud credits for their students. Each student will be given a fixed amount of starter credits to use Google Cloud Compute (GCP).
  • Students can also request credits from Google Cloud Compute.
  • If you are a company that can offer cloud computing credits, please contact reproducibility.challenge@gmail.com

Suggested Readings