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Creating Reproducible Data Science Workflows using Docker Containers

Description

Jupyter notebooks make it easy to create reproducible workflows that can be distributed across groups and organizations. This is a simple process provided that our end-users have access to the data along with a compatible Python environment. Learn how to use Docker to package a shareable image containing the libraries, code, and data required to reproduce every calculation.

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