Difference between revisions of "BigDataChallenge2014"

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== Link to the Big Data Challenge 2014 data set==
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== Links for the Big Data Challenge 2014 ==
 
 
[http://support.scinet.utoronto.ca/BigDataChallenge2014/BIG_DATA_CHLNG.xlsx BIG_DATA_CHLNG.xlsx]
 
 
 
  
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The [http://support.scinet.utoronto.ca/BigDataChallenge2014/BIG_DATA_CHLNG.xlsx BIG_DATA_CHLNG.xlsx Data Set]
  
 
== Computational tools and resources available to the students participating in the Challenge ==
 
== Computational tools and resources available to the students participating in the Challenge ==

Revision as of 09:42, 6 November 2014

Links for the Big Data Challenge 2014

The BIG_DATA_CHLNG.xlsx Data Set

Computational tools and resources available to the students participating in the Challenge

SAS resources to be provided to students

1) SAS University Edition: http://www.sas.com/en_us/software/university-edition.html

2) SAS On-Demand For Academics – This is a free cloud version of 5 of our products including Enterprise Miner – our foundation Data Mining tool. I will start a course for the competition http://www.sas.com/govedu/edu/programs/od_academics.html

3) Free E-Learning from U of T – See this PDF and the Access code is G70072789. There are a twelve different courses for students learn how to use SAS.

4) http://www.lexjansen.com – Great website for students to search and learn about different techniques of Analytics.

Open Source resources

1) R - Revolution R Open, from Revolution Analytics http://mran.revolutionanalytics.com/download/

2) Anaconda - a full-featured distribution of Python https://store.continuum.io/cshop/anaconda/