Using R to detect fraud at 1 million transactions per second

September 28, 2016
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Using R to detect fraud at 1 million transactions per second

In Joseph Sirosh's keynote presentation at the Data Science Summit on Monday, Wee Hyong Took demonstrated using R in SQL Server 2016 to detect fraud in real-time credit card transactions at a rate of 1 million transactions per second. The demo (which starts at the 17:00 minute mark) used a gradient-boosted tree model to predict the probability of a...

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Introducing the eRum 2016 sponsors

September 28, 2016
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Guest post by Maciej Beręsewicz. It has been a very active semester in Europe regarding R meetings. After two successful main events: satRday in Budapest, and EARL in London,...

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The Simpsons by the Data

September 28, 2016
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The Simpsons by the Data

The Simpsons needs no introduction. At 27 seasons and counting, it’s the longest-running scripted series in the history of American primetime television. The show’s longevity, and the fact that it’s...

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Efficient Data Manipulation with R Course | Milan

September 28, 2016
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Efficient Data Manipulation with R Course | Milan

Organize your data manipulation tasks in a standard way, write clean and efficient code, and build reproducible data management processes, using the most modern R tools: tidyr, dplyr and...

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The Financial Times uses R for Quantitative Journalism

September 27, 2016
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The Financial Times uses R for Quantitative Journalism

At the 2016 EARL London conference senior data-visualisation journalist John Burn-Murdoch, described how the Financial Times uses R to produce high-quality, striking data visualisations. Until recently, charts were the...

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First 10 Speakers announced for EARL Boston in November

September 27, 2016
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First 10 Speakers announced for EARL Boston in November

We are thrilled to announce our first batch of speakers for EARL Boston in November 2016. Keynotes Jenny Bryan and Ricardo Bion Jenny is the Associate Professor of Statistics...

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sparklyr — R interface for Apache Spark

September 27, 2016
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sparklyr — R interface for Apache Spark

We’re excited today to announce sparklyr, a new package that provides an interface between R and Apache Spark. Over the past couple of years we’ve heard time and time again...

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EARL London 2016 revisited – Day 2

September 27, 2016
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EARL London 2016 revisited – Day 2

This year’s conference was a great opportunity to catch up with friends and meet new people who are eager to talk about their work with R. We enjoyed the...

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Tagged NA values and labelled data #rstats

September 27, 2016
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Tagged NA values and labelled data #rstats

sjmisc-package: Working with labelled data A major update of my sjmisc-package was just released an CRAN. A major change (see changelog for all changes )is the support of the...

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Fitting a distribution in Stan from scratch

September 27, 2016
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Fitting a distribution in Stan from scratch

Last week the French National Institute of Health and Medical Research (Inserm) organised with the Stan Group a training programme on Bayesian Inference with Stan for Pharmacometrics in Paris....

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2016 UK Tour

September 26, 2016
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2016 UK Tour

I'll be in the UK next week doing three talks in three days: First, I'll be giving a talk at the London R-Ladies meetup on Monday October 3rd with...

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DataCamp Course

September 26, 2016
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DataCamp Course

Zachary Deane-Mayer, who collaborates on caret, has put together a DataCamp course on Machine Learning in R. Zach and DataCamp did a great job of developing a course that...

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Quick wordclouds from PubMed abstracts – using PMID lists in R

September 26, 2016
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Quick wordclouds from PubMed abstracts – using PMID lists in R

Wordclouds are one of the most visually straightforward, compelling ways of displaying text info in a graph. Of course, we have a lot of web pages (and even apps) that, given...

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Introduction to BiclustGUI

September 26, 2016
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Introduction to BiclustGUI

BiclustGUI in R Ewoud De Troyer, University of Hasselt (CenStat) Biclustering in a GUI & Growing a GUI together! Introduction We are happy to announce the first release of the BiclustGUI on CRAN...

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A book on RStan in Japanese: Bayesian Statistical Modeling Using Stan and R (Wonderful R, Volume 2)

September 26, 2016
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A book on RStan in Japanese: Bayesian Statistical Modeling Using Stan and R (Wonderful R, Volume 2)

Wonderful, indeed, to have an RStan book in Japanese: Kentarou Matsuura. 2016. Bayesian Statistical Modeling Using Stan and R. Wonderful R Series, Volume 2. Kyoritsu Shuppan Co., Ltd. Google...

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Upgrading to plotly 4.0 (and above)

September 26, 2016
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By Carson Sievert, lead Plotly R developer I’m excited to announce that plotly’s R package just sent its first CRAN update in nearly four months. To install the update,...

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Replicating Plots – Boxplot Exercises

September 26, 2016
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Replicating Plots – Boxplot Exercises

R’s boxplot function has a lot of useful parameters allowing us to change the behaviour and appearance of the boxplot graphs. In this exercise we will try to use...

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Machine Learning for Drug Adverse Event Discovery

September 26, 2016
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Machine Learning for Drug Adverse Event Discovery

We can use unsupervised machine learning to identify which drugs are associated with which adverse events. Specifically, machine learning can help us to create clusters based on gender, age,...

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When Trump visits… tweets from his trip to Mexico

September 25, 2016
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When Trump visits… tweets from his trip to Mexico

I’m sure many of my fellow Mexicans will remember the historically ill-advised (to say the least) decision by our President to invite Donald Trump for a meeting. Talking to some...

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Better Model Selection for Evolving Models

September 25, 2016
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Better Model Selection for Evolving Models

For quite some time now I have been using R’s caret package to choose the model for forecasting time series data. The approach is satisfactory as long as the...

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The biggest liars in US politics

September 25, 2016
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The biggest liars in US politics

Anyone that follows US politics will be aware of the tremendous changes and volatility that has struck the US political landscape in the past year. In this post, I...

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FileTable and storing graphs from Microsoft R Server

September 25, 2016
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FileTable and storing graphs from Microsoft R Server

FileTable has been around now for quite some time and and it is useful  for storing files, documents, pictures and and binary files in a designated SQL Server table...

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Re-introducing Radiant: A shiny interface for R

September 24, 2016
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Radiant is a platform-independent browser-based interface for business analytics in R. I first introduced Radiant through R-bloggers on 5/2/2015 and, according to Dean Attali, the post was reasonably popular....

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tint 0.0.1: Tint Is Not Tufte

September 24, 2016
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tint 0.0.1: Tint Is Not Tufte

A new experimental package is now on the ghrr drat. It is named tint which stands for Tint Is Not Tufte. It provides an alternative for Tufte-style html...

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Surveillance Out of the Box – The #Zombie Experiment

September 24, 2016
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Surveillance Out of the Box – The #Zombie Experiment

Abstract We perform a social experiment to investigate, if zombie related twitter posts can used as a reliable indicator for an early warning system. We show how such a system...

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Windows 10 anniversary updates includes a whole Linux layer – this is good news for data scientists

September 24, 2016
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If you are on Windows 10, no doubt you have heard that Microsoft included the bash shell in its 2016 Windows 10 anniversary update. What you may not know...

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Radial Stacked Area Chart in R using Plotly

September 24, 2016
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In this post we’ll quickly show how to create radial stacked ara charts in plotly. We’ll use the AirPassengers dataset. Inspired by Mike Bostocks post: http://bl.ocks.org/mbostock/3048740 Radial Stacked...

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My first Shiny App: control charts

September 24, 2016
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My first Shiny App: control charts

After having carefully followed the online official Shiny tutorial, I decided to make a quick try at making my very first Shiny App. I should say that I found...

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Environmental Monitoring App

September 23, 2016
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Environmental Monitoring App

Python, R, Qt, peewee, bokeh, pandas, SQLite plus couple of sleepless nights and here you are a сute app for the environmental monitoring needs )))Main window of the application

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