39 thoughts on “Best Programming Languages for Machine Learning”

  1. Pyhton is just high level scripting programming language binds C++ library. Currently in machine learning communinty python binding libraries better than js libraries. Because js binding libraries young and only support linux and modern MacOS. That is why pyhton is currently most common programming language for ML communinty. But in general Javascript is best language for programming and get paid for jobs. Since I learn Node.js (which is many years ago…) I quit Python and PHP forever. Python fans xD

  2. I have a love-hate relationship with Python. It's so damn useful and so well designed, with one exception: the syntax. Many people love it, but I can't stand it. Significant whitespace is my sworn enemy. Why do I need a backslash to spread my instruction over several lines? It's ugly and unintuitive. And the lack of brackets makes the code hard to read. When I look at a C-style language, I can see the structure at the first glance. Even in Lisp, I can make sense of the parentheses. But in Python I need to read every word carefully before I can see the source file as something more than a bunch of squiggly lines. The use of underscores instead of camelcase doesn't help either.

    I'm also not a big fan of Python's classes, but that's not that big of a deal.

  3. Why the only comment on R is that "it is slow"… without reasoning… hmmmm… maybe cuz this dude has a playlist on how to learn py, which he promotes in the end, and not htl R. Hmmmmm…

  4. Half of what I say is meaningless But I say it just to reach you

  5. Javascript will take over python in machine learning we have backend in nodejs and js in front end we will not be stopped until we rule the world 😂 the race to byte code 🙂

  6. I have personally worked with both R and python. If we talk about the part of visualization and statistical learning R is more powerful than python, in addition to having more complete libraries. At the time of entering deep learning python have more advantages over R. But I think that if we talk about very large volumes of data python is not exceeding too much with respect to R, in these cases is more powerful Julia

  7. I mostly use Haskell and I've got my own ML library written in it. Planning to migrate the core of it to OpenCL or GLSL so I can use some GPU accelleration (not CUDA because my GPU is unsupported)

  8. Where is my beloved Java that everyone tries to make fun off?

    Why is it my beloved you ask? Coz I had no choice but to learn it as a first language in crappy university. :'( And now I can't get motivation needed to get off that.

  9. Forty five years ago, I learnt Fortran. Most years in professional career went in other disciplines. In recent when I started renewing my programming skills to dabble in machine learning and artificial intelligence, I am confused with the rapidly changing scenarios and recommendations. Initially I learnt R. Then Python. Then Matlab. After that Java. When I thought it has to be Tensorflow, someone suggested Pytorch. Unfortunately my learning had been interrupted by other priorities and every time I come back after a break, the suggestion seems to change. At this rate I may keep updating my skills in basic programming language and not get on to my application. Of the choices you mention, there must be some bias for better suitability to some application domains. My interests are around language processing – OCR, Text to Speech, Speech recognition, and automated translation. I am considering switching to Pytorch. Any suggestions?

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