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IBM’s new open-source ‘COVID notebooks’ arrive chocked full of data for deep analysis

IBM today launched ‘COVID notebooks,’ an open-source data band-aid advised to help overwhelmed developers, researchers, and policy-makers.

When the big-wigs put their heads calm to work on communicable solutions, they need solid datasets full of up-to-date, organized, clean data. But coming up with these datasets is a awe-inspiring endeavor.

According to IBM:

The advice mural is overwhelming. A near-constant flow of data from assay studies, news outlets, social media, and health organizations make the task of allegory data into useful action nearly impossible. Developers and data scientists need answers to their questions about data sources, tools, and how to draw allusive and statistically valid abstracts from the ever-changing data.

Policy makers face agnate challenges. The United States has over 3,000 counties, each with a unique story of how COVID-19 is impacting its community.

IBM’s new COVID ability is an open-source Jupyter anthology absolute pandemic-related datasets and tools acquired from accurate data sources such as John Hopkins University, The New York Times, and the European Centre for Disease Prevention and Control.

As communicable data changes on a daily basis, the COVID anthology uses Elyra Anthology Pipelines Visual Editor and KubeFlow Pipelines to ensure advisers have clean, abreast datasets.

In other words, IBM’s taken as many pain-points out of the data accession and accomplishing action as possible.

This frees developers and advisers up to focus on the tasks of deep assay and anticipation clay and gives policy-makers quick, easy access to diminutive geographic details.

For more advice check out IBM‘s blog post here. You can access COVID notebooks here on GitHub.

Published June 25, 2020 — 16:11 UTC

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