Languages used

[gah44]

I was just wondering what languages different people use.

I don't yet know how poll works, but I will try to do one.

(OK, don't reply to this one. I will do another with better choices.)

[tzs29970]

Python is widely used in scientific computing. It should be on the list. Omitting it means you are going to get a lot of "other".

Mathematica probably should be there, too.

PL/1 is an odd inclusion. It is most widely know for business programming, and never really took off outside of mainframes.

APL would be good for the kind of things needed for this class (at least so far).

[gah44]

I could start a new one. I don't know how to delete one, though.

There is a maximum of 10 choices, which you have to specify
before specifying the choices. I could remove PL/I and add python.

Other than I did HW1 in awk, I could also remove that.

By the way, why 29970?

[fgpancorbo]

Definitely MATLAB. I got addicted to it during grad school and it's hard to get used to something else, especially for scientific computing. I haven't used Octave since I have my own MATLAB license.

[gah44]

This is a poll of languages used in solving homework problems where programming is required. It is intended to replace the one in the Homework 2 section.

You may choose more than one.

[gah44]

Thanks to all who have replied.

After some comments about choices, and because this is probably not the best place, I have reposted the poll in http://book.caltech.edu/bookforum/fo...play.php?f=140

(This was my first try at a poll.)

[jerrytsai]

Right now, I'm the only person reporting using R, which I am trying to learn, to substitute for my longtime usage of SAS.

Having taken Professor Ng's Machine Learning course on Coursera, I learned Octave (Matlab-like freeware), which I was using on Windows. I decided to work on this course-- Learning from Data-- on OS X and was preparing to install Octave when I decided to see which software packages are the most popular for machine learning.

After some exploration I found this interesting chart: Kagglers Favorite Tools

I then decided to jump into R (I have had considerable training in statistics, and was exposed to R during that training, but have been able to accomplish basically everything I ever needed to do with SAS.) Because I left myself not enough time, I had to use Octave to do the first problem set, but after the submission deadline I re-did it using R. I also used R to do the second problem set and plan to use it for the remainder of this course.

As a statistician, using R makes sense, because of the wealth of statistical tools it has. I have been trying to migrate to R from SAS for some time, and this course is a great MacGuffin to do so.

I decided to post about this decision-making in case anybody else was wondering about which software package to use and was wondering how we each chose the package we are using.

My longtime usage of SAS locked me in to that package for years, so the languages we choose to use initially often become the languages we use indefinitely. I am trying to reboot my choices by learning to use R for data analysis, Python for data processing, while only dabbling with Matlab/Octave.

However, as sets of data ever grow larger every day, I wonder which software package is (or will be) the fastest/most efficient. The amount of time a developer takes to construct an algorithm matters, but as N goes toward infinity, so does the amount of time the computer takes to implement that algorithm.

[tsukisan]

I used Mathematica ver 8. Really easy create code and visualize plots.

[ghuiber]

Mata. It's the matrix language embedded in Stata. See http://www.ssc.wisc.edu/sscc/pubs/4-26.htm for a nice intro.

[anachesa]

IMO Python is fine for relatively quick prototyping, but not for the serious data processing. High cost of function calls and quick stack overflow if you use recursion are the main problems I have with Python. It's just much slower than C++ or Java. Try to write recursive depth-search in Python and in C++, it is very educational.

Haven't used R yet, so no opinion there...