- Jupyter notebook that contains the steps of implementing a predictive model and has any descriptive comments that would help explain the working of the submitted solution
- Dockerfile and forecast.py those are needed to run your machine learning code
- Abstracts describing the approach. Any formats are accepted.
docker build -t no_flood_with_ai .
docker run --volume $(pwd)/datasets:/usr/src/app/datasets no_flood_with_ai 2020-10-11 2020-10-21
Note, you don't need to include datasets in a docker image.
As you can see, docker container runs with command line parameters that specifies the start and end of the period of data forecasts.