First Data Science Research Center Created in Seattle

Data Science Central, LLC, created the first research lab focused entirely on modern data science, big data and business analytics


ISSAQUAH, Wash., June 13, 2014 (GLOBE NEWSWIRE) -- via PRWEB - Data Science Central has created the first research lab focused entirely on modern data science, big data and business analytics. The research is developed by co-founder Dr. Vincent Granville, a former post-graduate from Cambridge University with more than 20 years of cross-industry experience in large and small companies including eBay, Wells Fargo, Visa, and Microsoft, and a long list of publications and start-ups.

The research center, also called data science research lab and abbreviated as DSRC publishes intellectual property (open patents that anyone can use), designs API's, machine learning algorithms prototyped on real data, and publishes articles related to Map-Reduce, robust scoring techniques for big data, clustering and creation of large taxonomies with natural language processing, detection of spurious correlations, new types of noise-resistant regression, new synthetic metrics to re-define correlations, variance and other statistical indicators in a way that is more robust, especially in the context of big data. The DSRC's mission is also to automate data science and statistical analyses, by producing efficient, scalable techniques that can be used as black boxes, in batch mode, by non-experts, or integrated to existing platforms.

The DSRC is an open research lab, vendor-neutral, government-neutral, and internally, privately funded. Anyone can post research papers, preprints and non commercial white papers discussing data science / big data new techniques, principles and methodology. We invite both academics, post-doc and PhD candidates as well as scientists from corporate, private or government research labs, to post their papers, to reach out to the largest community of analytic practitioners - DataScienceCentral.com - in a fraction of the time that it takes to get published in a traditional journal, and:

  • Quickly get peer reviews, via comments appended to your article, to improve your article before you submit it to a top journal
  • Gain more free insights and advice from experts, and connect with them
  • Publish material such as conference proceedings
  • A chance to be seen by many influential decision makers, get contacted for new opportunities, and boost your career

URL for the Data Science Research Center is datasciencecentral.com/group/research

This article was originally distributed on PRWeb. For the original version including any supplementary images or video, visit http://www.prweb.com/releases/2014/06/prweb11941421.htm


            

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