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Moving from exploration to production with Notebooks and Scripts

by Marshall M.

When it comes to data science code, there are two sides to the story. There’s the part where you do the exploratory science — and there’s the part where you put it in production. Last month, we announced that Civis Platform now allows data scientists to work in Jupyter notebooks, which is all about making data science exploration scalable, shareable,...

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From Science to Production: Unleash your Jupyter Notebooks

From Science to Production: Unleash your Jupyter Notebooks

by Lori E.

Data scientists are explorers. They use Jupyter Notebooks, one of the most popular environments for data science analysis, to begin work toward creative solutions to big problems. But once those solutions are discovered…what’s the next step? In order for data scientists to make a major impact, the creativity that starts in notebooks needs to find its way out to the...

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CivisML: Scikit-Learn at Scale

CivisML: Scikit-Learn at Scale

by Stephen H.

Late last year, my colleagues on the Social Science team were working on a new survey weighting scheme that would greatly improve the precision of our public opinion data. To make it work, they needed to fit dozens of models for each completed survey. Each survey asks multiple questions, each of which would need to be modeled individually, using an...

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