IBM launches open source novel Coronavirus data analysis

Source: IT Home

IBM's Open Source Data and AI Technology Center (CODAIT) debuted a new kit that helps developers and data scientists answer pandemic questions with Covid-Notebooks.

Covid-notebooks are designed to help complete the following tasks:

Get authoritative data about the current state of the outbreak,

Clean up the most serious data quality issues,

Organize the data into a format that is easy to analyze using tools like Pandas and Scikit-Learn,

And build an initial set of sample reports and graphs.

Taking care of these tasks frees up developers and data scientists to focus on advanced analysis and modeling tasks without worrying about data formatting and data cleansing, IBM says. The repository USES a dever-friendly Jupyter notebook to cover each initial data analysis step.

Also created data processing Pipelines using Elyra Notebook Visual Editor in Pipelines and KubeFlow Pipelines. Examples are as follows:

These pipes allow the user to re-run the entire extraction, transformation, and analysis workflow with the click of a button. "The tools in our repository use authoritative sources to generate comprehensive insights that decision makers can use to make real-time, critical decisions."

Frederick Reiss, principal Architect, IBM Open Source Data Center and AI Center: "For the analysis of the effect of COVID - 19 and tries to put forward feasible plan based on data data scientists and policy makers, relevant information can be overwhelming. From the research report, the news media, social media and health organization data almost continuously, this makes the data analysis for useful action mission impossible. Developers and data scientists need to answer them about data sources, tools, and how to constantly changing data in meaningful, statistically valid conclusion."

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