[R] Revolutions blog: September 2015 roundup

David Smith davidsmi at microsoft.com
Fri Oct 9 18:14:46 CEST 2015


Since 2008, Revolution Analytics (and now Microsoft) staff and guests have written about R every weekday at the Revolutions blog:
 http://blog.revolutionanalytics.com
and every month I post a summary of articles from the previous month of particular interest to readers of r-help. 

In case you missed them, here are some articles related to R from the month of September:

A tutorial on using R with Jupyter Notebooks http://blog.revolutionanalytics.com/2015/09/using-r-with-jupyter-notebooks.html and how to control the size of R graphics therein: http://blog.revolutionanalytics.com/2015/09/resizing-plots-in-the-r-kernel-for-jupyter-notebooks.html

A new version of Revolution R Open is available, featuring multi-threaded computing for R 3.2.2: http://blog.revolutionanalytics.com/2015/09/revolution-r-open-322-now-available.html 

One benefit of fitting statistical models to large data sets: learning curves http://blog.revolutionanalytics.com/2015/09/why-big-data-learning-curves.html

Using the AzureML package to publish R functions as web services: http://blog.revolutionanalytics.com/2015/09/publishing-r-models-as-a-service-with-azure-ml.html

The R Consortium forms a committee to oversee projects, headed by Hadley Wickham: http://blog.revolutionanalytics.com/2015/09/the-r-consortium-gears-up-for-business.html

Functions for interpolation in R: http://blog.revolutionanalytics.com/2015/09/interpolation-and-smoothing-functions-in-base-r.html

The EARL London conference (preview here: http://blog.revolutionanalytics.com/2015/09/a-preview-of-the-earl-conference.html) included many applications of R, from AstraZeneca, Allstate, Douwe Egberts coffee and others: http://blog.revolutionanalytics.com/2015/09/applications-of-r-at-earl-2015.html

A new online Data Science and Machine Learning course, featuring R and sponsored by Microsoft: http://blog.revolutionanalytics.com/2015/09/edx-data-science.html

Reading financial time series data into R with the zoo package: http://blog.revolutionanalytics.com/2015/09/reading-financial-time-series-with-r.html

An update to the checkpoint package brings support for knitr and rmarkdown documents in reproducible projects: http://blog.revolutionanalytics.com/2015/09/new-features-in-checkpoint-v0315-now-on-cran.html

The new Microsoft Data Science User Group Program offers sponsorships for R user groups worldwide: http://blog.revolutionanalytics.com/2015/09/the-new-microsoft-data-science-user-group-program.html

A series on model validation in R using: basic methods http://blog.revolutionanalytics.com/2015/09/how-do-you-know-if-yoru-model-is-going-to-work-part-1-the-problem.html; in-training set measures http://blog.revolutionanalytics.com/2015/09/how-do-you-know-if-your-model-is-going-to-work-part-2-in-training-set-measures.html; out-of-sample procedures http://blog.revolutionanalytics.com/2015/09/how-do-you-know-if-your-model-is-going-to-work-part-3-out-of-sample-procedures.html; and cross-validation techniques http://blog.revolutionanalytics.com/2015/09/how-do-you-know-if-your-model-is-going-to-work-part-4-cross-validation-techniques-1.html 

BlueSky Statistics, a new open-source GUI for R: http://blog.revolutionanalytics.com/2015/09/bluesky-statistics.html

Accessing data in Google spreadsheets with the googlesheets package: http://blog.revolutionanalytics.com/2015/09/using-the-googlesheets-package-to-work-with-google-sheets.html

Antony Unwin on the care of datasets in R packages: http://blog.revolutionanalytics.com/2015/09/looking-after-datasets.html

General interest stories (not related to R) in the past month included: building a scale model of the solar system (http://blog.revolutionanalytics.com/2015/09/a-scale-model-of-the-solar-system.html), a new way to visualize the DFT (http://blog.revolutionanalytics.com/2015/09/because-its-friday-visualizing-ffts.html), and a Portal-themed remodel (http://blog.revolutionanalytics.com/2015/09/portal-bedroom.html).

Meeting times for local R user groups (http://blog.revolutionanalytics.com/local-r-groups.html) can be found on the updated R Community Calendar at: http://blog.revolutionanalytics.com/calendar.html

If you're looking for more articles about R, you can find summaries from previous months at http://blog.revolutionanalytics.com/roundups/. You can receive daily blog posts via email using services like blogtrottr.com, or join the Revolution Analytics mailing list at http://revolutionanalytics.com/newsletter to be alerted to new articles on a monthly basis.

As always, thanks for the comments and please keep sending suggestions to me at davidsmi at microsoft.com or via Twitter (I'm @revodavid).

Cheers,
# David


-- 
David M Smith <davidsmi at microsoft.com>
R Community Lead, Microsoft
Twitter: @revodavid
Blog:  http://blog.revolutionanalytics.com <http://blog.revolutionanalytics.com/>
We’re hiring! http://azuremljobs.github.io/


More information about the R-help mailing list