Reflections on Julia
Julia is a new language that could become the goto choice for scientific computing, machine learning, data mining, large-scale linear algebra, distributed and parallel computing. It uses LLVM-based just-in-time (JIT) compilation, has the speed of C and the dynamism of Ruby. Contributors of Julia wrote a manifesto to explain their motivation for creating yet another programming language. Jeff Bezanson, Stefan Karpinski, Viral Shah and Alan Edelman highlight Python’s annoying dependencies, JVM’s unnecessary overhead, and the debugging pain of distributed systems like Hadoop as just of few of the reasons why Julia exists.

40 maps that explain the internet
The internet increasingly pervades our lives, delivering information to us no matter where we are. It takes a complex system of cables, servers, towers, and other infrastructure, developed over decades, to allow us to stay in touch with our friends and family so effortlessly. Here are 40 maps that will help you better understand the internet — where it came from, how it works, and how it’s used by people around the world.

The Surprising Things You Don’t Know About Big Data
Big Data is an industry growing at light speed, and rapidly entering into our everyday lexicon. So to help out those not in-the-know in order to ease into technology jargon, here’s a simple resource developed by our friends over at Adeptia. The infographic covers the basics of what exactly big data is, how big data is used, companies by the estimated number of servers, along with a breakdown of the past, present and future of big data. Enjoy!

Building OpenBLAS-based Rblas.dll for 64-bit R for Windows: R ≥ 3.2.0
With the release of R 3.2.0 going to significantly change how to compile R from source for Windows, it is a good time to update the steps of how to build an OpenBLAS-based Rblas. Of course, the previous caveats still apply: I am not a programmer nor do I play one on the internet so I probably cannot debug any issue anyone may have. Use the BLAS at your own risk and reward. If you use it win the Nobel prize, the credit is all yours (and that of R-core and the OpenBLAS team). If your computer explodes into a pile of slag, opening a dimensional portal to the netherworld and starting the zombie apocalypse, you’re on your own—although I’d appreciate a quick e-mail telling me to run for the hills. The instructions generally assume that you are familiar with compiling programs on Windows, especially versions of R. If not, it is crucial to read and understand the R Installation and Administration manual, especially the portions on compiling for Windows. Even though I have done so scores of times over the years, I still keep the manual open when I am performing a new compilation.

Helping Your Organization Migrate to R
As the R programming environment has grown in capability and popularity, so have the number of organizations planning to migrate to it from proprietary tools. I’ve helped members of various organizations transition from SAS, SPSS and/or Stata to R, and the process typically involves the following steps:
1) Begin with the most important question: who should you migrate to R?
2) —Motivate people to migrate.
3) Use training & documentation that leverages what they already know, that speaks their language.
4) —Provide in-house tech support.
5) Match your staff’s current work style, work flow and output.
6) Migrate one step at a time if possible.
7) —Convert your programs or use conversion services.

One-proportion z test in R
For quite a while, I’ve been confused by the behavior of the prop.test function in R: 1) the p-values always seem to be slightly off, and 2) the confidence intervals never seem to be symmetric around my estimate of the population proportion. Today, I decided I was going to figure out what was up… and whether I should trust my own analytical calculations for this test or what I get in R. I started by checking R Bloggers to see if anyone had explored this problem, but I only found one post about the two proportion z-test, and found none focusing on the one proportion z-test.

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