I created a docker image with python libraries and Jupyter.
I start the container with the option -p 8888:8888
, to link ports between host and container.
When I l
Check out the Torus project that Manifold open sourced recently. We wanted an easy way for our ML engineers to hit the ground running on new projects with a consistent development environment across the entire team. This Python cookiecutter will scaffold out a new project structure for you that includes a Dockerfile that uses a pre-baked ML dev image that we put in Docker Hub and a Docker Compose config that takes care of all the port forwarding for you. The config is written to pick an open port on your host machine to forward to the notebook server running on 8888 inside the container. No more hassle running multiple notebook servers on your machine! Check it out hopefully this is helpful!
Github repo: https://github.com/manifoldai/docker-cookiecutter-data-science
Why we built it (w/ demo): https://medium.com/manifold-ai/torus-a-toolkit-for-docker-first-data-science-bddcb4c97b52