by Ramkumar Chandrasekeran, Software Engineer - Microsoft R Tiger Team DeployR Enterprise is designed to deliver analytics solutions at scale to whomever needs it: inside or outside the enterprise. It also guarantees secure delivery of your analytics via DeployR web services. These secure web services integrate seamlessly with existing enterprise ... [Read more...]

by Joseph Rickert Last week in a webinar, Burtch Works, an Illinois based executive recruiting firm that specializes in finding analytic talent, released the results of their third annual survey of "quantitative business professionals". Other than having attended this webinar, I have no knowledge of Burtch Works, but I am ... [Read more...]

by Mike Wise, Data Scientist / Solution Architect – MCS Incubation Services Background Building energy consumption is a huge component of energy consumption. In the USA for example, around 40 percent of the energy consumed is in buildings, and as the USA consumes something like 25 percent of the worlds energy, it is clear ... [Read more...]

by Joseph Rickert New R packages keep rolling into CRAN at a prodigious rate: 184 in May, 195 in June and July looks like it will continue the trend. I spent some time sorting through them and have picked out a few that that are interesting from a data science point of ... [Read more...]

by Joseph Rickert Last week, I mentioned a few of the useR tutorials that I had the opportunity to attend. Here are the links to the slides and code for all but two of the tutorials: Regression Modeling Strategies and the rms Package - Frank Harrell Using Git and GitHub ... [Read more...]

by Konstantin Golyaev, Data Scientist at Microsoft I recently participated in an internal one-day Microsoft R Server (MRS) hackathon. For an experienced base R user but a complete MRS novice, this turned out to be an interesting challenge. R has fantastic and unparalleled set of tools for exploratory data analysis, ... [Read more...]

by Joseph Rickert Over the years I have seen several excellent tutorials at useR!conferences that were not only very satisfying "you had to be there" experiences but were also backed up with meticulously prepared materials of lasting value. This year, quite a few useR!20i6 tutorials measure up to ... [Read more...]

by Joseph Rickert Just about two and a half years ago I wrote about some resources for doing Bayesian statistics in R. Motivated by the tutorial Modern Bayesian Tools for Time Series Analysis by Harte and Weylandt that I attended at R/Finance last month, and the upcoming tutorial An ... [Read more...]

by Lourdes O. Montenegro Lourdes O. Montenegro is a PhD candidate at the Lee Kuan Yew School of Public Policy, National University of Singapore. Her research interests cover the intersection of applied data science, technology, economics and public policy. Many of us now find it hard to live without a ... [Read more...]

by Joseph Rickert It is always a delight to discover a new and useful R package, and it is especially nice when the discovery comes with at context and testimonial to its effectiveness. It is also satisfying to be able to check in once in awhile and get an idea ... [Read more...]

by Dmitry Pechyoni, Microsoft Data Scientist The New York City taxi dataset is one of the largest publicly available datasets. It has about 1.1 billion taxi rides in New York City. Previously this dataset was explored and visualized in a number of blog posts, where the authors used various technologies (e.... [Read more...]

by Joseph Rickert IBM Joins the R Consortium This past Monday at the Spark Summit in San Francisco IBM announced that it had joined the R Consortium as a "Platinum" member. This is very good news with respect to the development and growth of the R language, the health of ... [Read more...]

by Max Kuhn: Director, Nonclinical Statistics, Pfizer Many predictive and machine learning models have structural or tuning parameters that cannot be directly estimated from the data. For example, when using K-nearest neighbor model, there is no analytical estimator for K (the number of neighbors). Typically, resampling is used to get ... [Read more...]

by Joseph Rickert The model table on the caret package website lists more that 200 variations of predictive analytics models that are available withing the caret framework. All of these models may be prepared, tuned, fit and evaluated with a common set of caret functions. All on its own, the table ... [Read more...]

by John Mount Ph. D. Data Scientist at Win-Vector LLC In her series on principal components analysis for regression in R, Win-Vector LLC's Dr. Nina Zumel broke the demonstration down into the following pieces: Part 1: the proper preparation of data and use of principal components analysis (particularly for supervised learning ... [Read more...]

by Joseph Rickert R / Finance 2016 lived up to expectations and provided the quality networking and learning experience that longtime participants have come to value. Eight years is a long time for a conference to keep its sparkle and pizzazz. But, the conference organizers and the UIC have managed to create ... [Read more...]

by John Mount Ph. D. Data Scientist at Win-Vector LLC In part 2 of her series on Principal Components Regression Dr. Nina Zumel illustrates so-called y-aware techniques. These often neglected methods use the fact that for predictive modeling problems we know the dependent variable, outcome or y, so we can use ... [Read more...]

by Joseph Rickert For quite a few years now we have attempted to maintain the Revolution Analytics' Local R User Group Directory as the complete and authoritative list of R user groups. Meetup groups make this list in one of two ways: we discover the group because they have a ... [Read more...]

John Mount Ph. D. Data Scientist at Win-Vector LLC Win-Vector LLC's Dr. Nina Zumel has just started a two part series on Principal Components Regression that we think is well worth your time. You can read her article here. Principal Components Regression (PCR) is the use of Principal Components Analysis (... [Read more...]

by Joseph Rickert What makes for a good R package? With over 8,000 packages up on CRAN the quantity of packages is clearly not an issue for R users. Developing an instinct to recognize quality, however, both requires and deserves some effort. I regularly spend time on Dirk Eddelbuettel’s CRANberries ... [Read more...]