Adapted from repo by Will Koehrsen

Show how you can repeatably and scalability share analysis using Docker and and OSS data science packages in the Python ecosystem.

Simpliest way to run the application is to execute the command below for the Bokeh Application. You can then access the application at http://localhost:8080:

docker run -d -p 8080:8080 registry.gitlab.zoll-lifevest.com/research/mli-codebank/ml-viz-sample:1.0.0-app

You can also explore with the underlying Jupyter Notebooks by running. You can then access the notebooks at http://localhost:8888:

docker run -d -p 8888:8888 registry.gitlab.zoll-lifevest.com/research/mli-codebank/ml-viz-sample:1.0.0-notebook

When running notebook may ask you to enter name because workspace is in use. Just enter arbitrary text in textbox.

1. Bokeh Python repo by Will Koehrsen
2. Data Visualizations in Bokeh
3. Jupyter Stacks
4. Bokeh