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DESCRIPTION:Click for Latest Location Information: http://edw2015.dataversity.net/sessionPop.cfm?confid=87&proposalid=7198\nCollecting Big Data is easy (well...). Now finding the patterns in them and translating them into real insight is easy, too. While troves of data and disparate sources were enough to scare you, we will present easy to implement case studies of diverse statistical analytics and machine learning algorithms that allow practitioners to make actionable inference from their data, painlessly.\nOpen-source computer science communities for R and Python have developed powerful statistical libraries that are unprecedented in their reliability, transparency, potential, and now accessibility and ease of use. This presentation will cover the following big-data and statistical learning capabilities in R and Python: \n-visualizations of summary statistics, \n-classification and regression problems, \n-dimensionality reduction,\n-how to implement the above in hadoop/mapreduce ecosystems and NoSQL capabilities in our case studies.\nAttendees will leave with an understanding of a breadth of statistical learning capabilities and with a general impression of the ease to which these techniques can be applied to diverse domains and data types, across varied data disciplines.
DTSTART:20150401T093000
SUMMARY:Powerful Machine Learning Anyone Can Do
DTEND:20150401T101459
LOCATION: See Description
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