This is a boilerplate repository for my docker environments for ML.

Build and run a docker container with a specific ML setup. Use the working-dir folder to mount your project folder into the docker container.

Clone or fork this repository.

1. Update the Dockerfile according to your project needs.
2. Create a .env file using the env-SAMPLE as a template.

$ ./build.sh

$ docker build -t <docker-build-name>  .

$ ./run.sh

$ docker run -p 8888:8888 -v ./working-dir:/home/jovyan/working-dir <docker-build-name>