3111 search results for "TwitteR"

In case you missed it: March 2017 roundup

April 10, 2017
By

In case you missed them, here are some articles from March of particular interest to R users. A tutorial and comparison of the SparkR, sparklyr, rsparkling, and RevoScaleR packages for using R with Spark. An analysis of Scrabble games between AI players. The doAzureParallel package, a backend to "foreach" for parallel computations on Azure-based clusters. The UK government project...

Read more »

How and when: ridge regression with glmnet

April 10, 2017
By
How and when: ridge regression with glmnet

@drsimonj here to show you how to conduct ridge regression (linear regression with L2 regularization) in R using the glmnet package, and use simulations to demonstrate its relative advantages over ordinary least squares regression.  Ridge regression Ridge regression uses L2 regularisation to weight/penalise residuals when the parameters of a regression model are being learned. In the context of...

Read more »

#4: Simpler shoulders()

April 8, 2017
By
#4: Simpler shoulders()

Welcome to the fourth post in the repulsively random R ramblings series, or R4 for short. My twitter feed was buzzing about a nice (and as yet unpublished, ie not-on-CRAN) package https://github.com/dirkschumacher/thankr by Dirk Schumacher which compiles a a list of packages (ordered by maintainer count) for your current session (or installation or ...) with a...

Read more »

The faces of R, analyzed with R

April 7, 2017
By
The faces of R, analyzed with R

Maëlle Salmon recently created a collage of profile pictures of people who use the #rstats hashtag in their Twitter bio to indicate their use of R. (I've included a detail below; click to see the complete version at Maëlle's blog.) Naturally, Maëlle created the collage using R itself. Matching Twitter bios were found using the search_users function in the...

Read more »

R benchmark for High-Performance Analytics and Computing (II): GPU Packages

April 7, 2017
By
R benchmark for High-Performance Analytics and Computing (II): GPU Packages

Share This: 1. Overview In the previous post (here), we have analyzed the performance gain of R in the heterogeneous system by accelerators, including NVIDIA GPU and Intel Xeon Phi. Furthermore, GPU accelerated packages can greatly improve the performance of R. Figure 1 shows the download statistics of CRAN over the years. Obviously, GPU is

Read more »

The Run(chart)ing Man

April 5, 2017
By
The Run(chart)ing Man

Measurement for improvement in healthcare with R and Qlik - My not so secret obsession Anyone in the small subset of the Earth’s population who both read this blog AND follow me on Twitter will know that I spend a lot of time at work eithe...

Read more »

R track on exercism.io

April 4, 2017
By
R track on exercism.io

The devil is in the details! - As I’ve said before, when it comes to programming I’m a firm believer in the “learn by doing” approach. exercism.io is a project which exemplifies this. I came across exercism.io earlier this year while ex...

Read more »

Key Phrase Extraction from Tweets

April 2, 2017
By
Key Phrase Extraction from Tweets

In a previous post of mine published at DataScience+, I analyzed the text of the first presidential debate using relatively simple string manipulation functions to answer some high level questions from the available text. In this post, we leverage a few other NLP techniques to analyze another text corpus – A collection of tweets. Given Related Post

Read more »

Simple Offline Airport Wi-Fi Tracker in R

April 2, 2017
By

@visualisingdata rebroadcast this tweet today: Wireless Passwords From Airports And Lounges Around The World https://t.co/OV0WJfwj8E— deb verhoeven (@bestqualitycrab) April 2, 2017 The Google Maps interface is a bit meh and the “formatted” data is also a bit meh but the data is useful when travelling (NOTE: always use a VPN in airports on both your... Continue reading...

Read more »

Using R: Don’t save your workspace

April 2, 2017
By
Using R: Don’t save your workspace

To everyone learning R: Don’t save your workspace. When you exit an R session, you’re faced with the question of whether or not to save your workspace. You should almost never answer yes. Saving your workspace creates an image of your current variables and functions, and saves them to a file called ”.RData”. When you

Read more »

Recent popular posts

Sponsors

Never miss an update!
Subscribe to R-bloggers to receive
e-mails with the latest R posts.
(You will not see this message again.)

Click here to close (This popup will not appear again)