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Docker for Data Scientists: Part 3

Tue 21 August 2018 by Jeff Fischer

This is a why-to and how-to guide to using Docker in your data science workflow. It is the companion text to the talk I gave at the PyBay Conference in San Francisco on August 18th. Given its length, I have spread this text out over a three-post series. This is …

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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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