openkbs/scikit-docker repository overview

⁠scikit

##Components:

• ref: https://github.com/davidshen84/docker-scikit-learn⁠
• ref: https://github.com/davidshen84/docker-jupyter⁠

⁠Pull the image from Docker Repository

docker pull openkbs/scikit

⁠Login password/token (from jupyter screen)

Token authentication is enabled. You need to open the notebook server with its first-time login token in the URL, or enable a password in order to gain access. After you get in the container, the command to show token is

jupyter notebook list

will show you the URLs of running servers with their tokens, which you can copy and paste into your browser. For example:

Currently running servers:
http://localhost:8888/?token=c8de56fa... :: /Users/you/notebooks

Or you can paste just the token value into the password field on this page.

Cookies are required for authenticated access to notebooks.

⁠Or, just show the docker log to see the token

docker ps -a |grep scikit (to see the container id)
then,
docker logs <container_id>

⁠Connect to scikit Docker

host/port=> 0.0.0.0:18888 login/passwd=> (see above)

⁠Base the image to build add-on components

FROM openkbs/scikit

⁠Run the image

Then, you're ready to run:

• make sure you create your work directory, e.g., ./data

mkdir ./data
docker run -d --name my-scikit -p 18888:8888 openkbs/scikit

⁠Build and Run your own image

Say, you will build the image "my/scikit".

docker build -t my/scikit .

To run your own image, say, with some-scikit:

mkdir ./data
docker run -d --name some-scikit -p 18888:8888 my/scikit

⁠Shell into the Docker instance

docker exec -it some-scikit /bin/bash