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Big Data, Analytics and the Architecture of Computation

Whitaker Institute for Innovation and Societal Change, NUI Galway

Thursday, 14 November 2013 from 09:30 to 13:30 (GMT)

Big Data, Analytics and the Architecture of Computation

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Registration ticket Ended Free  

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Event Details

Workshop jointly hosted by the Irish Centre for High End Computing (ICHEC) and the Social Sciences Computing Hub at the Whitaker Institute

The half-day workshop will introduce some novel statistical methods and computational techniques involved in big data analytics, including the issue of cleaning the data sets and automated classification, and visualization. The workshop will also discuss both the conventional and emerging innovative computational solutions for working with big data.

The computations will be implemented in the R environment and the extensibility of the environment will be discussed. 

This workshop will be beneficial to a wide range of researchers across Social Sciences, Humanities, Natural and Physical Sciences.

 

Programme:

09:30 - Introduction to data analytics  What is it, why is it important, where is it used

09:50 - Data analytics: Computation  The R environment, Visualization and Extensibility

10:15 - BREAK

 

10:45 - Introduction to techniques and their implementation   Cleaning, basic stats, regression, time series, automated classification

11:45 - BREAK

 

12:00 – Big data’ and computer architecture   What is ‘big data’, where they come from, the conventional and emerging computing solutions

12:30 - Q&A, discussion

 

13:00 - END/LUNCH

 

Speakers:

Dr. Adam Ralph, ICHEC

Dr. Bruno Voisin, ICHEC

Dr. Michael Browne, ICHEC

Dr. Srinivas Raghavendra, NUIG

 

Contact: Gráinne Larkin, Whitaker Institute grainne.larkin@nuigalway.ie 

 

 

Do you have questions about Big Data, Analytics and the Architecture of Computation? Contact Whitaker Institute for Innovation and Societal Change, NUI Galway

When & Where


CA107, St Anthony's, Cairnes Building



Thursday, 14 November 2013 from 09:30 to 13:30 (GMT)


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