ICML is changing its constitution

ICML is changing its constitution Andrew McCallum has been leading an initiative to update the bylaws of IMLS, the organization which runs ICML. I expect most people aren’t interested in such details. However, the bylaws change rarely and can have an impact over a long period of time so they do have some real importance. I’d like to hear comment from anyone with a particular interest before this year’s ICML. In my opinion, the most important aspect of the bylaws is the at-large election of members of the board which is preserved. Most of the changes between the old and new versions are aimed at better defining roles, committees, etc… to leave IMLS/ICML better organized. Anyways, please comment if you have a concern or thoughts.
Original Post: ICML is changing its constitution

Take the R Consortium survey on R

Since its foundation just a little over two years ago, the R Consortium has been dedicated to providing support to the R Project and the R community. Already, the R Consortium has channeled the contributions from its corporate members to fund more than 25 projects, working groups, and community initiatives. Recently funded initiatives include a code coverage tool for R, improved connectivity between R and databases, new methods for handling spatial data, the R-hub package builder, and the SatRdays and R-Ladies community programs. (Many of these projects were presented at the recent useR!2017 conference in Brussels, which was awesome to see.) Now, the R Consortium would like to year from you, the R user community, to help guide it directions. Please take a few minutes to take the R Consortium’s Survey on R, and share your thoughts on the past, present and…
Original Post: Take the R Consortium survey on R

UseR! 2017 live-stream starts July 5

The useR!2017 conference, the annual meeting of R users worldwide and the largest to date, is sold completely sold out. But for those that couldn’t make it to Brussels, Microsoft will be live-streaming the conference at aka.ms/useRConference-live. Bookmark that page and follow along during the conference starting with the opening of the main program at 9:00 AM Brussels time (UTC+2hrs) on Wednesday, July 5.  To help you plan your viewing schedule, you can find the complete useR!2017 schedule here. (You can also find links to keynotes and presentations from my Microsoft colleagues here.) As with last year’s conference (you can watch the proceedings from useR!2016 here), the recordings of the presentations will available for on-demand viewing a couple of weeks after the conference. Also, new to this year, all of the tutorials will also be recorded (though not livestreamed). You can…
Original Post: UseR! 2017 live-stream starts July 5

R 3.4.1 "Single Candle" released

The R core team announced today the release of R 3.4.1 (codename: Single Candle). This release fixes a few minor bugs reported after the release of R 3.4.0, including an issue sometimes encountered when attempting to install packages on Windows, and problems displaying functions including Unicode characters (like “日本語”) in the Windows GUI. The other fixes are mostly relevant to packages developers and those building R from source, and you can see the full list in the announcement linked below. At the time of writing, Windows builds are already available at the main CRAN cloud mirror, and the Debian builds are out, but Mac builds aren’t there quite yet (unless you want to build from source). Binaries for all platforms should propagate across the mirror network over the next couple of days. r-announce mailing list: R 3.4.1 is released
Original Post: R 3.4.1 "Single Candle" released

Machine Learning the Future Class

Machine Learning the Future Class This spring, I taught a class on Machine Learning the Future at Cornell Tech covering a number of advanced topics in machine learning including online learning, joint (structured) prediction, active learning, contextual bandit learning, logarithmic time prediction, and parallel learning. Each of these classes was recorded from the laptop via Zoom and I just uploaded the recordings to Youtube. In some ways, this class is a followup to the large scale learning class I taught with Yann LeCun 4 years ago. The videos for that class were taken down(*) so these lectures both update and replace shared subjects as well as having some new subjects. Much of this material is fairly close to research so to assist other machine learning lecturers around the world in digesting the material, I’ve made all the source available as…
Original Post: Machine Learning the Future Class

Microsoft R Open 3.4.0 now available

Microsoft R Open (MRO), Microsoft’s enhanced distribution of open source R, has been upgraded to version 3.4.0 and is now available for download for Windows, Mac, and Linux. This update upgrades the R language engine to R 3.4.0, reduces the size of the installer image, and updates the bundled packages. R 3.4.0 (upon which MRO 3.4.0 is based) is a major update to the R language, with many fixes and improvements. Most notably, R 3.4.0 introduces a just-in-time (JIT) compiler to improve performance of the scripts and functions that you write. There have been a few minor tweaks to the language itself, but in general functions and packages written for R 3.3.x should work the same in R 3.4.0. As usual, MRO points to a fixed CRAN snapshot from May 1 2017, but you can use the built-in checkpoint package to access packages…
Original Post: Microsoft R Open 3.4.0 now available

AzureDSVM: a new R package for elastic use of the Azure Data Science Virtual Machine

by Le Zhang (Data Scientist, Microsoft) and Graham Williams (Director of Data Science, Microsoft) The Azure Data Science Virtual Machine (DSVM) is a curated VM which provides commonly-used tools and software for data science and machine learning, pre-installed. AzureDSVM is a new R package that enables seamless interaction with the DSVM from a local R session, by providing functions for the following tasks: Deployment, deallocation, deletion of one or multiple DSVMs; Remote execution of local R scripts: compute contexts available in Microsoft R Server can be enabled for enhanced computation efficiency for either a single DSVM or a cluster of DSVMs; Retrieval of cost consumption and total expense spent on using DSVM(s). AzureDSVM is built upon the AzureSMR package and depends on the same set of R packages such as httr, jsonlite, etc. It requires the same initial set up on Azure Active…
Original Post: AzureDSVM: a new R package for elastic use of the Azure Data Science Virtual Machine

R and Python support now built in to Visual Studio 2017

The new Visual Studio 2017 has built-in support for programming in R and Python. For older versions of Visual Studio, support for these languages has been available via the RTVS and PTVS add-ins, but the new Data Science Workloads in Visual Studio 2017 make them available without a separate add-in. Just choose the “Data Science and analytical applications” option during installation to install everything you need, including Microsoft R Client and the Anaconda Python distribution. If you’re new to the Python capabilities in Visual Studio, this Lap Around Python in VS2017 will provide an overview of the capabilities. The capabilities of RTVS 1.0 — described in detail in this announcement for Visual Studio 2015 — are now available in Visual Studio 2017. These capabilities are now available in all editions, including Visual Studio Community 2017 which you can download for free here. For…
Original Post: R and Python support now built in to Visual Studio 2017

Introducing the AzureSMR package: Manage Azure services from your R session

by Alan Weaver, Advanced Analytics Specialist at Microsoft Very often data scientists and analysts require access to back-end resources on Azure. For example, they may need to start a virtual machine or resize a Hadoop cluster. This typically requires making a request to the IT department and patiently waiting.  AzureSMR is a simple R package that enables those users to do many of those operations themselves. It’s very easy to script commonly-used functions which can be run without having to navigate the portal or wizards. AzureSMR uses the Azure Systems Management API and leverages standard packages such as httr, so it can easily run in any R session (you don’t need Microsoft R Server).  You can also manage multiple Azure subscriptions from within the same session. The AzureSMR functions currently addresses the following Azure Services: Azure Blob: List, Read and…
Original Post: Introducing the AzureSMR package: Manage Azure services from your R session