Reproducible Data Science in Python

07/08/2019
1:30-5:30
The expectation of reproducibility in scientific work has been long established, and, increasingly, communities and funding sources are actually demanding it. Within the Python ecosystem, there are a variety of tools available to support reproducible data science, but choosing and using one is not always straightforward. In this tutorial, we will take a closer look at the concept of _reproducibility_, and, we will examine the technologies that provide building blocks and survey the landscape of tools. We spend the majority of the time looking at two solutions in particular, Code Ocean and Renku, and work through end-to-end scenarios in both.

Prerequisites:

NumPy, SciPy, Pandas

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