Difference between revisions of "BigDataChallenge2014"
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* The [http://cysjournal.ca/page/bigdatachallenge Challenge Website] | * The [http://cysjournal.ca/page/bigdatachallenge Challenge Website] | ||
* The [http://support.scinet.utoronto.ca/BigDataChallenge2014/BIG_DATA_CHLNG.xlsx Data Set] | * The [http://support.scinet.utoronto.ca/BigDataChallenge2014/BIG_DATA_CHLNG.xlsx Data Set] | ||
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== Computational tools and resources available to the students participating in the Challenge == | == Computational tools and resources available to the students participating in the Challenge == | ||
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4) http://www.lexjansen.com – Great website for students to search and learn about different techniques of Analytics. | 4) http://www.lexjansen.com – Great website for students to search and learn about different techniques of Analytics. | ||
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===Open Source resources=== | ===Open Source resources=== | ||
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2) Anaconda - a full-featured distribution of Python https://store.continuum.io/cshop/anaconda/ | 2) Anaconda - a full-featured distribution of Python https://store.continuum.io/cshop/anaconda/ | ||
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+ | == Information Sessions == | ||
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+ | * [Slides] from the second information session. |
Revision as of 09:46, 6 November 2014
Links for the Big Data Challenge 2014
- The Challenge Website
- The 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/
Information Sessions
- [Slides] from the second information session.