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The Three R’s

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I’ve read that ten years is a common “lifetime” for a technology. Whether that’s true, or not, it seems to be the case with me. After beginning with BASIC & S/360 Assembler, I programmed in C/C++ from ~ 1985 until 1995, then in Java until 2006, and since then I’ve been programming primarily in Ruby/Rails.

For a number of years, I’ve felt the need to consider what my next primary language should be, and after experimenting with various lisps, Haskell and OCaml, I found that Racket is the best fit for me. I’m still very much in learning mode now, but I hope to be using Racket professionally in 2016.

Despite the fact that Racket is significantly faster than Ruby, I do occasionally have compute-intensive tasks that require more raw speed, so for a high performance language to maximize all the cores at my disposal, I’ve recently settled on Rust. I expect I will mostly be developing in Racket with the occasional performance hungry lib/program in Rust.

A current interest of mine is statistical programming, big data, data science, etc. Both R and Python are on the short list here with Julia trailing behind. I really like what I’ve seen in Julia, and I wouldn’t at all be surprised if I end up there; however, as a newbie learning the field, I think I’ll find much better support (educational info, existing libraries, community support, etc.) with R, so I’m starting with that until I’m convinced of switching.

At my stage, the language isn’t as important as becoming more educated in probability & statistics, machine learning, etc.

I didn’t plan it this way, but it appears that I’m going to be spending a lot of time with Racket, Rust and R.



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