This tutorial will show you how to integrate docker into your data science workflow. docker is an open source tool that makes it easy to build, deploy and run applications using a container framework. If you do any of the following, you can use docker to make your life easier:
- share and reproduce your analysis
- run large scale data cleaning tasks
- build dashboards and publish models
Clone the repo to your machine
git clone https://github.com/harnav/pydata-docker-tutorial.git
In this tutorial, we will go over three points
- Running a container
- Reproducible environments
- Deploying models
For more detailed instructions, check out: