Articles by Guest Blogger

How to give money to the R project

December 11, 2018 | Guest Blogger

by Mark Niemann-Ross, an author, educator, and writer who teaches about R and Raspberry Pi at LinkedIn Learning I spend a LOT of time at, in particular the sections for documentation and CRAN. But I hadn’t spent much time in the other areas: R Project, R Foundation, ... [Read more...]

DataExplorer: Fast Data Exploration With Minimum Code

February 8, 2018 | Guest Blogger

by Boxuan Cui, Data Scientist at Smarter Travel Once upon a time, there was a joke: In Data Science, 80% of time spent prepare data, 20% of time spent complain about need for prepare data. — Big Data Borat (@BigDataBorat) February 27, 2013 According to a Forbes article, cleaning and organizing data is the most ... [Read more...]

An introduction to seplyr

December 14, 2017 | Guest Blogger

by John Mount, Win-Vector LLC [`seplyr`]( is an [`R`]( package that supplies improved standard evaluation interfaces for many common data wrangling tasks. The core of `seplyr` is a re-skinning of [`dplyr`]('s functionality to `seplyr` ... [Read more...]

How to make Python easier for the R user: revoscalepy

November 28, 2017 | Guest Blogger

by Siddarth Ramesh, Data Scientist, Microsoft I’m an R programmer. To me, R has been great for data exploration, transformation, statistical modeling, and visualizations. However, there is a huge community of Data Scientists and Analysts who turn to Python for these tasks. Moreover, both R and Python experts exist ... [Read more...]

Recap: EARL Boston 2017

November 9, 2017 | Guest Blogger

By Emmanuel Awa, Francesca Lazzeri and Jaya Mathew, data scientists at Microsoft A few of us got to attend EARL conference in Boston last week which brought together a group of talented users of R from academia and industry. The conference highlighted various Enterprise Applications of R. Despite being a ... [Read more...]

Tutorial: Deep Learning with R on Azure with Keras and CNTK

August 9, 2017 | Guest Blogger

by Le Zhang (Data Scientist, Microsoft) and Graham Williams (Director of Data Science, Microsoft) Microsoft's Cognitive Toolkit (better known as CNTK) is a commercial-grade and open-source framework for deep learning tasks. At present CNTK does not have a native R interface but can be accessed through Keras, a high-level API ... [Read more...]

Data Science Accelerator for Credit Risk Prediction

July 12, 2017 | Guest Blogger

by Fang Zhou, Data Scientist; Graham Williams, Director of Data Science, all at Microsoft Credit Risk Scoring is a classic but increasingly important operation in banking as banks are becoming far more risk careful when lending for mortgages, credit card payments or other commercial purposes, in an industry known for ... [Read more...]

XGBoost support added to Rattle

July 7, 2017 | Guest Blogger

by Fang Zhou, Data Scientist; and Graham Williams, Director of Data Science, all at Microsoft Rattle — the R Analytical Tool To Learn Easily — is a popular open-source GUI for data mining using R. It presents statistical and visual summaries of data, transforms data that can be readily modelled, builds both ... [Read more...]

Running your R code on Azure with mrsdeploy

March 22, 2017 | Guest Blogger

by John-Mark Agosta, data scientist manager at Microsoft Let’s say you’ve built a model in R that is larger than you can conveniently run locally, and you want to take advantage of Azure’s resources simply to run it on a larger machine. This blog explains how to ... [Read more...]

AUC Meets the Wilcoxon-Mann-Whitney U-Statistic

March 15, 2017 | Guest Blogger

by Bob Horton, Senior Data Scientist, Microsoft The area under an ROC curve (AUC) is commonly used in machine learning to summarize the performance of a predictive model with a single value. But you might be surprised to learn that the AUC is directly connected to the Mann-Whitney U-Statistic, which ... [Read more...]
1 2

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)