337 search results for "hadoop"

The rise of R as the language of analytics

November 22, 2013
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It's no coincidence that while the usage of the R language is skyrocketing (as shown in the recent Rexer Analytics and KDNuggets polls), the growth in data scientist jobs is also skyrocketing. R is the lingua franca of data science, and as the pervasive statistical software in the academic sector, there's a steady-stream of newly-minted graduates trained in R,...

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In case you missed it: October 2013 Roundup

November 11, 2013
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In case you missed them, here are some articles from October of particular interest to R users: Joe Rickert recounts the R presence at the Strata + Hadoop World conference, including slides from the R and Hadoop tutorial. Hadley Wickham's favorite tools, gadgets and software (including of course R). Revolution R Enterprise 7 is announced, with updated R engine...

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R jobs (September, October 2013)

November 5, 2013
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R_jobs

R-bloggers is offering an “R jobs” post, that will be published once every month (or other month). If you are interested in offering a job to be posted on r-bloggers, please e-mail me at: [email protected] (please write in the subject line the text “R job” so I could have easy e-mail filtering on it ). statistics. com Occasional part-time...

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Dream Team – combining Tableau and R

November 3, 2013
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Dream Team – combining Tableau and R

Last quarter was a bit too busy to write some new blog post because of a new job. And changing the job often come along with changing the tools you work with. That was my way to Tableau. Tableau is one of the new stars in the BI/Analytics world and definitely worth a look. The people at Tableau...

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What’s new in Revolution R Enterprise? Webinar November 5

November 1, 2013
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Revolution R Enterprise 7 is a major update to Revolution Analytics' flagship predictive analytics software. Not only does it include the latest release of Open Source R (providing compatability with more than 6,000 user-contributed packages), it also adds in-Hadoop and in-database predictive modeling with big data, new statistical capabilities, and drag-and-drop workflow building via integration with Alteryx. You can...

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Video: Revolution R Enterprise 7 interview on theCUBE

October 29, 2013
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I'm in New York City for the Strata + Hadoop World conference, and last night I got the chance to stop by theCUBE for an live interview about Revolution R Enterprise 7. You can watch the full interview below, or click the links on the topics to skip ahead. Many thanks to Dave Vellante of Wikibon and John Furrier...

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Myown way to Data Science

October 28, 2013
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Myown way to Data Science

In my last post, I point the Road to data science, imagined by Swami. I think this road is too long and we can't make any difference  between the basics (we have to know) and the advanced(it's important to know, bu if not, it doesn't matter).So I'...

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Introducing Revolution R Enterprise 7

October 28, 2013
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We're very excited to formally announce that Revolution R Enterprise 7 is here! This release includes the latest release of Open Source R (R 3.0.2). It brings R and the massively-parallel R functions from Revolution Analytics to Cloudera and Hortonworks in-Hadoop, and in-database on Teradata. It also brings a new drag-and-drop user interface via integration with Alteryx, and a...

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My experience of learning R – from basic graphs to performance tuning

October 23, 2013
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My experience of learning R – from basic graphs to performance tuning

BackgroundR as some of you may know is a statistical and graphics programming language (see Wikipedia ) used by academia and recently by IT professionals of our ever growing software industry. There is a sudden demand for Data Scientists, Data Analysts and Statisticians with a background in R among other things data and development related subjects. I have...

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Video: Time-to-event models

October 21, 2013
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If you're trying to predict when an event will occur (for example, a consumer buying a product) or trying to infer why events occur (what were the factors that led to a component failing?), time-to-event models are a useful framework. These models are closely related to survival analysis in life sciences, except that the outcome of interest isn't "time...

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