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Docker for Data Scientists: Part 2

Sat 18 August 2018 by Jeff Fischer

This is part 2 of my why-to and how-to guide to using Docker in your data science workflow. It is the companion text to the talk I will be giving at the PyBay Conference in San Francisco this afternoon (August 18th). The final post in this series will appear on …

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How to Build a Reproducible Data Science Workflow

Thu 19 April 2018 by Jeff Fischer

Why care about reproducibility? You probably have heard about reproducibility in the context of scientific experiments. It is about providing enough information to the readers of a publication to enable them to run the same experiment and see the same results. This includes information about experimental procedures, materials used, and …

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