1062 search results for "RStudio"

A Few Notes on UseR! 2014

July 25, 2014
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A Few Notes on UseR! 2014

It has been a month since the UseR! 2014 conference, and I'm probably the last one who writes about it. UseR! is my favorite conference because it is technical and not too big. I have completely lost interest in big and broad conferences like JSM (to me, it has become Joint Sightseeing Meetings). Karl has written two blog posts...

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Things to try after useR! – Part 1: Deep Learning with H2O

July 25, 2014
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Things to try after useR! – Part 1: Deep Learning with H2O

Annual R User Conference 2014The useR! 2014 conference was a mind-blowing experience. Hundreds of R enthusiasts and the beautiful UCLA campus, I am really glad that I had the chance to attend! The only problem is that, after a few days of non-stop R talks, I was (and still am) completely overwhelmed...

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Announcing Shiny Server Pro 1.2

July 24, 2014
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Announcing Shiny Server Pro 1.2

RStudio is very pleased to announce the general availability of Shiny Server Pro 1.2. Download a free 45 day evaluation of Shiny Server Pro 1.2 Shiny Server Pro 1.2 adds support for R Markdown Interactive Documents in addition to Shiny applications. Learn more about Interactive Documents by registering for the Reproducible Reporting webinar August 13

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Interactive visualization of non-linear logistic regression decision boundaries with Shiny

Interactive visualization of non-linear logistic regression decision boundaries with Shiny

(skip to the shiny app) Model building is very often an iterative process that involves multiple steps of choosing an algorithm and hyperparameters, evaluating that model / cross validation, and optimizing the hyperparameters. I find a great aid in this process, for classification tasks, is not only to keep track of the accuracy across models, »more

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Agent Based Models and RNetLogo

July 24, 2014
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Agent Based Models and RNetLogo

by Joseph Rickert If I had to pick just one application to be the “killer app” for the digital computer I would probably choose Agent Based Modeling (ABM). Imagine creating a world populated with hundreds, or even thousands of agents, interacting with each other and with the environment according to their own simple rules. What kinds of patterns and...

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Six of One (Plot), Half-Dozen of the Other

July 24, 2014
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Six of One (Plot), Half-Dozen of the Other

This is a guest post by Randy Zwitch (@randyzwitch), a digital analytics and predictive modeling consultant in the Greater Philadelphia area. Randy blogs regularly about Data Science and related technologies at http://randyzwitch.com. He’s blogged at Bad Hessian before here. For those of you with WordPress blogs and have the Jetpack Stats module installed, you’re intimately familiar… Continue reading →

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magrittr: Simplifying R code with pipes

July 23, 2014
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magrittr: Simplifying R code with pipes

R is a functional language, which means that your code often contains a lot of ( parentheses ). And complex code often means nesting those parentheses together, which make code hard to read and understand. But there's a very handy R package — magrittr, by Stefan Milton Bache — which lets you transform nested function calls into a simple...

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New data packages

July 23, 2014
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New data packages

I’ve released four new data packages to CRAN: babynames, fueleconomy, nasaweather and nycflights13. The goal of these packages is to provide some interesting, and relatively large, datasets to demonstrate various data analysis challenges in R. The package source code (on github, linked above) is fully reproducible so that you can see some data tidying in

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Announcing Packrat v0.4

July 22, 2014
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Announcing Packrat v0.4

We’re excited to announce a new release of Packrat, a tool for making R projects more isolated and reproducible by managing their package dependencies. This release brings a number of exciting features to Packrat that significantly improve the user experience: Automatic snapshots ensure that new packages installed in your project library are automatically tracked by

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Introducing tidyr

July 22, 2014
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Introducing tidyr

tidyr is new package that makes it easy to “tidy” your data. Tidy data is data that’s easy to work with: it’s easy to munge (with dplyr), visualise (with ggplot2 or ggvis) and model (with R’s hundreds of modelling packages). The two most important properties of tidy data are: Each column is a variable. Each

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