For anyone else who hadn’t heard of JupyterLite — it’s like Jupyter Notebook/Lab, but it runs completely in your browser. No servers, no backend — everything executes client-side.
Python on Web Assembly has to be really slow.
GNU Octave Meets JupyterLite: Compute Anywhere, Anytime
11–20 of 44 posts
Re: GNU Octave Meets JupyterLite: Compute Anywhere, Anytime
#12For anyone else who hadn't heard of Octave, it's an open source near-clone of the proprietary MATLAB: https://en.wikipedia.org/wiki/GNU_Octave
Early versions of Andrew Ng's ML MOOC used Octave, if you are looking for examples and exercises. YouTube playlist: https://www.youtube.com/playlist?list=PLiPvV5TNogxIS4bHQVW4p...
I was in one of those early cohorts that used Octave, one of the things the course had to deal with was that at the time (I don't know about now) Octave did not ship with an optimization function suitable for the coursework so we ended up using an implementation of `fmincg` provided along with the homework by the course staff. If you're following along with the lectures, you might need to track down that file, it's probably available somewhere.
Using Octave for a beginning ML class felt like the worst of both worlds - you got the awkward, ugly language of MATLAB without any of the upsides of MATLAB-the-product because it didn't have the GUI environment or the huge pile of toolbox functions. None of that is meant as criticism at Octave as a project, it's fine for what it is, it just ended up being more of a stumbling block for beginners than a booster in that specific context.
Re: GNU Octave Meets JupyterLite: Compute Anywhere, Anytime
#13For anyone else who hadn’t heard of JupyterLite — it’s like Jupyter Notebook/Lab, but it runs completely in your browser. No servers, no backend — everything executes client-side.
Python on Web Assembly has to be really slow.
It’s slower than native, sure — but for education, it’s a game changer. Students can open a notebook in any browser, on any device (even a Chromebook or iPad), and start coding instantly — no installs, no setup issues. Perfect for workshops, classrooms, or sharing interactive tutorials. It runs real Python, so you can teach core concepts, plotting, and even simple data analysis right in the browser. For heavier computation, you’d still offload to a remote kernel, but for learning and experimentation, it’s more than fast enough.
Re: GNU Octave Meets JupyterLite: Compute Anywhere, Anytime
#14Earlier quoted context omitted.
"near clone" is a bit exaggerated. As much as I'm a free software zealot, I don't think Octave comes close to matlab yet (provided you do anything a bit more advanced than the practical of some courses) See https://stackoverflow.com/questions/12084246/differences-bet...
I don’t think Matlab or Octave are great languages for software engineering. Actually, these languages are like example #1 of the difference between engineering software vs software engineering: they are excellent tools for writing, like, 10-100 line numerical experiments. Anyone who runs up against a limitation of Octave has probably hit the point where they should consider switching, but not to Matlab or some other…
They are never meant for general software engineer but for numerical analysis/data analysis and engineering. In fact they are quite horrible for writing general software code -- the APIs for IO and HTTP requests are very lacking compared what you can find in other languages, for example.
Re: GNU Octave Meets JupyterLite: Compute Anywhere, Anytime
#15This is great! I always wanted a GNU Octave transpiled to other languages. Octave could be embedded as a C library for some time: https://stackoverflow.com/questions/9246444/how-to-embed-the... https://docs.octave.org/latest/Standalone-Programs.html There is an OpenCL package to provide GPU acceleration: https://gnu-octave.github.io/packages/ocl/ Unfortunately it looks like they did it wrong, by providing explicit GP…
> alternative methods ... DSLs
This strongly agrees with you: https://alexalejandre.com/languages/end-of-programming-langs...
Re: GNU Octave Meets JupyterLite: Compute Anywhere, Anytime
#16For anyone else who hadn't heard of Octave, it's an open source near-clone of the proprietary MATLAB: https://en.wikipedia.org/wiki/GNU_Octave
I'm not a Matlab user, but from what I can tell, even if the language can be cloned, there's a lot more to Matlab: It's a GUI driven software suite, with a lot of pre-written apps that eliminate the need for coding in many cases.
It comes with vendor support and "official-ness" for lack of a better word.
Things are changing rapidly in this area but it wasn't very long ago that most people reacted to open-source software as something weird that shouldn't be trusted.
Re: GNU Octave Meets JupyterLite: Compute Anywhere, Anytime
#17For anyone else who hadn't heard of Octave, it's an open source near-clone of the proprietary MATLAB: https://en.wikipedia.org/wiki/GNU_Octave
"near clone" is a bit exaggerated. As much as I'm a free software zealot, I don't think Octave comes close to matlab yet (provided you do anything a bit more advanced than the practical of some courses) See https://stackoverflow.com/questions/12084246/differences-bet...
People who use MATLAB use it for the toolboxes.
The language itself is awful.
Re: GNU Octave Meets JupyterLite: Compute Anywhere, Anytime
#18Earlier quoted context omitted.
Early versions of Andrew Ng's ML MOOC used Octave, if you are looking for examples and exercises. YouTube playlist: https://www.youtube.com/playlist?list=PLiPvV5TNogxIS4bHQVW4p...
I was in one of those early cohorts that used Octave, one of the things the course had to deal with was that at the time (I don't know about now) Octave did not ship with an optimization function suitable for the coursework so we ended up using an implementation of `fmincg` provided along with the homework by the course staff. If you're following along with the lectures, you might need to track down that file, it's p…
It’s nice to know that someone else suffered this pain. And that i bet on PGMs which really turned out to be the wrong horse…
Re: GNU Octave Meets JupyterLite: Compute Anywhere, Anytime
#19For anyone else who hadn’t heard of JupyterLite — it’s like Jupyter Notebook/Lab, but it runs completely in your browser. No servers, no backend — everything executes client-side.
Python on Web Assembly has to be really slow.
Hmm. Do we expect X on Y to have run times more like X*Y or max(X,Y)? Or maybe some more complicated combination because you have to pay both their overheads but then once things start cranking you are just paying the per-element cost of one of the languages…
Re: GNU Octave Meets JupyterLite: Compute Anywhere, Anytime
#20For anyone else who hadn't heard of Octave, it's an open source near-clone of the proprietary MATLAB: https://en.wikipedia.org/wiki/GNU_Octave
Scilab is another MATLAB clone, but emphasizes features rather than compatibility.