Ask HN: Languages to learn in 2019 for Data Science?
Besides Python, any languages that can make a difference for data science? What would you recommend and why?!
If you already know Python, learning how to do the same things in a different environment doesn't really add a skill to your resume. It probably means you can apply for more jobs/work on different projects but for each job/project you would be the same candidate as before. Almost like branching out your skill tree rather than extending it.
On the other hand, at a time when importing a library and throwing it on a dataset (without understanding what it actually does) is becoming easier, having a comprehensive understanding of probability, statistics, calculus and linear algebra would be a huge differentiator.
As far as languages go, Scala comes up a lot in data science job postings where I live, but my experience is limited only to trying out the Scala API of Spark. Maybe someone with more experience can shed some light on this.
* Great environment with RStudio
* Awesome plotting and visualization with ggplot
* Very welcoming community with a very diverse background ranging from social science to quantitative finance
Basically for everything except deep learning R is a great alternative to python. If you rely on advanced statistics I think R is the way to go.
Being able to do these things thoroughly and quickly, has (in my experience) been the most important technical skill for getting data science right, regardless of the language production models end up getting deployed in.
Having said that tinyverse basically calls methods written in C and has a beautiful syntax. As Rcpp let’s you write whatever needs to go quickly in c++ then easily expose it in R.
My experience has been the exact opposite. R is great as an interactive statistical environment. But if you need to build data-intensive applications in it - it's still powerful but somewhat slow and also a bit of a mess: many exceptions, special cases, strange design choices and multiple ways to do the same thing. It can get the job done, but there is an unpleasant learning curve to get used to all the weirdness.
I'd only recommend Matlab for data science if you already know it (say you're studying engineering) and are looking to start with data science.
Also, if you like Matlab/know it well, you might want to look into the deep learning toolbox (if you have access to it). I found I was able to do all the stuff I was doing in keras with Matlab. Haven't learned to recreate all the stuff I was doing with tensor flow there, but it might be possible.
Others on the internet say:
"Teaching a python Dev Clojure would be small fraction of there time.
Some of the libraries people reach for in Python for DS aren't even necessary in Clojure. Pandas is a good example of this.
Data Science is as wide a field as programming, there are lots of things that a JVM based language would be great at."
Source: https://www.reddit.com/r/Clojure/comments/7jdaac/clojure_dat...
IMO learn a little lisp ASAP