4 ms·

You said it yourself—Octave isn't trendy or cool.

jhbadger 10y ago
The problem is I think Octave missed its window. 20 years ago when I was in grad school, everybody was using Matlab and a competitive open source version would have been a killer app. I looked into Octave at the time, but it was basically a toy at that point. I looked into it recently, and it really has come a long way, and even has an official GUI similar to Matlab's, but these days Matlab is kind of fading out and R is what everybody seems to be using.
- viraptor 10y ago
  I did my uni ~10 years ago and I made a point of using Octave when everyone else was using Matlab. It worked just great for all the ODE and statistics exercises. Nobody else used it though.
- photojosh 10y ago
  And 10 years ago when I was in grad school (dropped out though), Python was on the rise with numpy and matplotlib. Coming from a programming background, it was an easy choice and I'm still using those today. They've got more usable for people with less programming experience with Jupyter notebooks etc. Was briefly tempted by Octave, but it just didn't happen.
- adw 10y ago
  Different communities. Matlab and Octave are big among capital-E engineers, R is for statistics and fights with Python.
  - zild3d 10y ago
    Exactly, and matlab is growing in engineering schools and big engineernig firms, not fading out
- knlje 10y ago
  0 years ago when I was in grad school, everybody was still using Matlab. Ok, some used R and NumPy but 80% Matlab. Such a collection of sparse matrix routines (direct solve, iterative solve, preconditioning, eigensolvers, SVD) is very useful in applied sciences.
- petters 10y ago
  Or Python. I switched from Matlab to Python and Numpy and Matplotlib and Jupyter a few years ago and haven't looked back. They really are better in many ways.
- GFK_of_xmaspast 10y ago
  20 years ago when I was in grad school I did use octave to do my research, and it was 'mostly fine'. (Also I discovered that a couple of the matlab toolboxes I needed were just .m files and there was no technical reason that I couldn't just copy them into a local directory for octave to find; I consider this no worse than 'morally iffy' considering that we had a matlab site license)
Isamu 10y ago
Hey, I used it in Andrew Ng's Machine Learning course on Cousera. It was that or Matlab. Nothing trendier than ML, so I'd recommend going that direction.
- tylerhou 10y ago
  You can use Python; someone created bindings: https://github.com/mstampfer/Coursera-Stanford-ML-Python https://github.com/mstampfer/Coursera-Stanford-ML-Python

The problem is I think Octave missed its window. 20 years ago when I was in grad school, everybody was using Matlab and a competitive open source version would have been a killer app. I looked into Octave at the time, but it was basically a toy at that point. I looked into it recently, and it really has come a long way, and even has an official GUI similar to Matlab's, but these days Matlab is kind of fading out and R is what everybody seems to be using.

viraptor 10y ago
I did my uni ~10 years ago and I made a point of using Octave when everyone else was using Matlab. It worked just great for all the ODE and statistics exercises. Nobody else used it though.
photojosh 10y ago
And 10 years ago when I was in grad school (dropped out though), Python was on the rise with numpy and matplotlib. Coming from a programming background, it was an easy choice and I'm still using those today. They've got more usable for people with less programming experience with Jupyter notebooks etc. Was briefly tempted by Octave, but it just didn't happen.
adw 10y ago
Different communities. Matlab and Octave are big among capital-E engineers, R is for statistics and fights with Python.
- zild3d 10y ago
  Exactly, and matlab is growing in engineering schools and big engineernig firms, not fading out
knlje 10y ago
0 years ago when I was in grad school, everybody was still using Matlab. Ok, some used R and NumPy but 80% Matlab. Such a collection of sparse matrix routines (direct solve, iterative solve, preconditioning, eigensolvers, SVD) is very useful in applied sciences.
petters 10y ago
Or Python. I switched from Matlab to Python and Numpy and Matplotlib and Jupyter a few years ago and haven't looked back. They really are better in many ways.
GFK_of_xmaspast 10y ago
20 years ago when I was in grad school I did use octave to do my research, and it was 'mostly fine'. (Also I discovered that a couple of the matlab toolboxes I needed were just .m files and there was no technical reason that I couldn't just copy them into a local directory for octave to find; I consider this no worse than 'morally iffy' considering that we had a matlab site license)

Isamu 10y ago

Hey, I used it in Andrew Ng's Machine Learning course on Cousera. It was that or Matlab. Nothing trendier than ML, so I'd recommend going that direction.

tylerhou 10y ago
You can use Python; someone created bindings: https://github.com/mstampfer/Coursera-Stanford-ML-Python https://github.com/mstampfer/Coursera-Stanford-ML-Python