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Data is big
&amp;amp;quot;The future is here. It's just not evenly distributed yet.&amp;amp;quot; - William Gibson     :::: Follow this topic for fresh resources and ideas related to Data Science, Machine Learning, Algorithms and #bigdata :::: <a href="http://www.dataisbig.co" rel="nofollow">http://www.dataisbig.co</a>/
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SparkR: Distributed data frames with Spark and R

SparkR: Distributed data frames with Spark and R | Data is big | Scoop.it
(This article was first published on Revolutions, and kindly contributed to R-bloggers)
R is now integrated with Apache Spark, the open-source cluster computing framework.
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An R Introduction to Statistics | R #Tutorial I #datascience #openaccess

An R Introduction to Statistics | R #Tutorial I #datascience #openaccess | Data is big | Scoop.it
An R introduction to statistics that explains basic R concepts and illustrates with statistics textbook homework exercises.

Via luiy
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luiy's curator insight, November 30, 2013 1:24 PM

Welcome to R Tutorial. We provide an introduction to the R programming language, and illustrate its use by solving elementary statistics textbook exercises. Beyond the basics, we also cover topics of GPU computing in R. Hope you find the material helpful, and this site serves the intended purpose of being a stepping stone for further study.

 

Thank you for visiting us. Please bookmark us and come back often.

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Togaware: One Page R: A Survival Guide to Data Science with R

ukituki's insight:

Welcome to One Page R. This compendium of modules weaves together a collection of tools for the data miner, data scientist, and decision scientist. The tools are all part of the RStatistical Software Suite.

 

Each module begins with a Lecture on the topic, followed by a OnePageR oriented introduction to the topic. The OnePageR consists of multiple, one page recipes that cover many aspects of the topic. It can be worked through by the student and then used as a reference guide. Each page aims to be a bite sized chunk for hands-on learning, building on what has gone before. A laboratory session then follows, where the student is epxected to complete the tasks and submit material for assessment.

 

The R code sitting behind each OnePageR module is also provided and can be run standalone to replicate the material presented in the module.

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Forecasting time series using R

Forecasting time series using R | Data is big | Scoop.it

Melbourne R Users' Group

 

ukituki's insight:

"I will look at the various facilities for time series forecasting available in R, concentrating on the forecast package. This package implements several automatic methods for forecasting time series including forecasts from ARIMA models, ARFIMA models and exponential smoothing models. I will also look more generally at how to go about forecasting non-seasonal data, seasonal data, seasonal data with high frequency, and seasonal data with multiple frequencies. Examples will be taken from my own consulting experience. I will give an overview of what’s possible and available and where it is useful, rather than give the mathematical details of any specific time series methods."

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