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The Evolution of Data Science Workbench | Uber Engineering BlogUber EngineeringSearch iconSearch iconUber Chevron ArrowUber Chevron ArrowUber Chevron ArrowUber Chevron Arrow

In October 2017, we published an article introducing Data Science Workbench (DSW), our custom, all-in-one toolbox for data science, complex geospatial analytics, and exploratory machine learning. It centralizes everything required to perform data preparation, ad-hoc analyses, model prototyping, workflow scheduling, dashboarding, and collaboration in a single-pane, web-based graphical user interface.  In this article, we reflect on the evolution of DSW over the last 3 years. We review our journey by looking at how DSW’s usage has evolved to include and supercharge the workflows of more than just data scientists, dive into how the choices we made when designing the platform

3 mentions: @atg_abhishek
Date: 2021/06/10 09:57

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@atg_abhishek "The dependency management tool chosen for managing Python environments was used to be PIP with requirement.txt. However, requirement.txt doesn’t exhaustively lock the versions of a package’s all dependencies. Therefore installing the same set of packa..." t.co/ayuqITAP2F

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