6 ms·

Checked if he moved it away from Matlab, and yes he did! That's what steered me away from his course.

by cypress66 4y ago

quux 4y ago
What's the class using now?
- oogetyboogety 4y ago
  10 bucks says it's python
  - rashkov 4y ago
    “Graded assignments and lectures have been rebuilt to teach in Python instead of Octave“
    - shankr 4y ago
      I almost forgot it was in Octave. I had done it when it was offered for the first time by stanford.
      - rashkov 4y ago
        I really like the commitment to open source (and student accessibility) that led the course author to choose octave.
lern_too_spel 4y ago
The programming assignments were one or two lines in Octave. They'll turn into 10 lines of Python with indentation errors. Python is a worse pedagogical language for any course in applied linear algebra.
- bonniemuffin 4y ago
  OTOH, the time I spent learning Octave/Matlab for Andrew Ng's course was 100% wasted time, because I've never used it again in the 10+ years since I took the class, whereas time spent learning Python would've been useful to me in myriad other ways.
  - melling 4y ago
    The amount of Octave needed for the class was manageable. Learning Octave made me wish all languages supported matrices, vectors, and the necessary operations.
  - nytesky 4y ago
    So sad to hear Mariah disparaged. I’m an Gen X engineer and Matlab is one of our first languages. Use it today still in aerospace but I would imagine Python suits software shops much better. Does Python handle matrix math as well?
    - bowsamic 4y ago
      MATLAB is still in heavy use in physics, mainly for experiments bc of simulink and the control systems toolbox
      - jcadam 4y ago
        When I worked on the GPS III program back in the day, my job largely consisted of translating scientists' Matlab script into Ada.
        FabienC 4y ago
        Now there's an app for that https://www.adacore.com/qgen https://www.adacore.com/qgen :)
      - LosWochosWeek 4y ago
        I hate MATLAB with a burning passion, but Simulink is a damn good piece of software.
arberx 4y ago
You can do them in python and submit them! https://github.com/dibgerge/ml-coursera-python-assignments https://github.com/dibgerge/ml-coursera-python-assignments
jcadam 4y ago
I took it when it was still in Matlab :) Haven't used Matlab since.
deleted 4y ago
[deleted]
wcoenen 4y ago
I had no problems completing the original course in Octave. No Matlab license required.
czbond 4y ago
Question: Why was the original version in Matlab? I am familiar with Python, R, and others.... I get that those languages until recently might not have been great over the ancient predecessors (LISP, etc) for ML related. But I've never seen actual production anything in Matlab. Did Matlab provide something at the time others did not? If so, how did they transfer MatLab to running production models? Or did they create a model with basic outcomes - and then code a representation of it in C++, etc?
- telotortium 4y ago
  Before Python (Numpy/Scipy) really came into its own (which didn't quite happen until early 2010s), Matlab was among the easiest-to-use scripting languages for writing scientific computing programs. I was in university (Bachelor's + Masters) from 2007-2012 and learned Matlab extensively in my numerical computing classes (I was a Physics major, for what that's worth). When you're ready to run your scientific computing codes on a supercomputer cluster, you'd usually rewrite it in C++ or Fortran (my research group used the latter), but to develop and debug at a small scale, you'd usually use Matlab, although the younger people like me might use Numpy, and there were one or two people who used Mathematica even for numerical computing (as opposed to symbolic algebra, which everybody used Mathematica for). It was around the time I was in university that Python really matured for numerical computing, but professors (as opposed to grad students) were likely to be already familiar with Matlab, so there wasn't much reason for them to learn Python. Andrew Ng was already a mid-career researcher when he made his course, which was probably based on older materials (I also learned basic neural networks in my numerical computing class in 2008), so it made sense for him to continue to use Matlab, especially because Octave exists as an open-source reimplementation of the basic functionality. These days, you wouldn't use anything else but Python for ML, at least until you really productionize the implementation at a large scale, at which case you might rewrite in C++ or Rust (I don't know if they even bother rewriting these days when most of the computation happens in GPUs or TPUs). And it's my understanding, although I'm not really too familiar these days, that Matlab has mostly pivoted into providing a toolbox of all sorts of esoteric numerical methods for engineering-related tasks like finite element analysis, as well as hardware simulation (using Simulink).
rg111 4y ago
I did everything in Octave. And it was a great learning experience. Octave is very easy to learn if you have previous programming experience. You won't _write_ programs a lot. There will be cookie-cutter code, and you will fill in some blanks. A line here a line there. Trust me, Octave wasn’t a deal-breaker if you tried. And a lot of formulae were the code.

Checked if he moved it away from Matlab, and yes he did! That's what steered me away from his course.

quux 4y ago

What's the class using now?

oogetyboogety 4y ago
10 bucks says it's python
- rashkov 4y ago
  “Graded assignments and lectures have been rebuilt to teach in Python instead of Octave“
  - shankr 4y ago
    I almost forgot it was in Octave. I had done it when it was offered for the first time by stanford.
    - rashkov 4y ago
      I really like the commitment to open source (and student accessibility) that led the course author to choose octave.

lern_too_spel 4y ago

The programming assignments were one or two lines in Octave. They'll turn into 10 lines of Python with indentation errors. Python is a worse pedagogical language for any course in applied linear algebra.

bonniemuffin 4y ago
OTOH, the time I spent learning Octave/Matlab for Andrew Ng's course was 100% wasted time, because I've never used it again in the 10+ years since I took the class, whereas time spent learning Python would've been useful to me in myriad other ways.
- melling 4y ago
  The amount of Octave needed for the class was manageable. Learning Octave made me wish all languages supported matrices, vectors, and the necessary operations.
- nytesky 4y ago
  So sad to hear Mariah disparaged. I’m an Gen X engineer and Matlab is one of our first languages. Use it today still in aerospace but I would imagine Python suits software shops much better. Does Python handle matrix math as well?
  - bowsamic 4y ago
    MATLAB is still in heavy use in physics, mainly for experiments bc of simulink and the control systems toolbox
    - jcadam 4y ago
      When I worked on the GPS III program back in the day, my job largely consisted of translating scientists' Matlab script into Ada.
      - FabienC 4y ago
        Now there's an app for that https://www.adacore.com/qgen https://www.adacore.com/qgen :)
    - LosWochosWeek 4y ago
      I hate MATLAB with a burning passion, but Simulink is a damn good piece of software.

arberx 4y ago

You can do them in python and submit them! https://github.com/dibgerge/ml-coursera-python-assignments https://github.com/dibgerge/ml-coursera-python-assignments

jcadam 4y ago

I took it when it was still in Matlab :) Haven't used Matlab since.

deleted 4y ago

[deleted]

wcoenen 4y ago

I had no problems completing the original course in Octave. No Matlab license required.

czbond 4y ago

Question: Why was the original version in Matlab? I am familiar with Python, R, and others.... I get that those languages until recently might not have been great over the ancient predecessors (LISP, etc) for ML related. But I've never seen actual production anything in Matlab. Did Matlab provide something at the time others did not? If so, how did they transfer MatLab to running production models? Or did they create a model with basic outcomes - and then code a representation of it in C++, etc?

telotortium 4y ago
Before Python (Numpy/Scipy) really came into its own (which didn't quite happen until early 2010s), Matlab was among the easiest-to-use scripting languages for writing scientific computing programs. I was in university (Bachelor's + Masters) from 2007-2012 and learned Matlab extensively in my numerical computing classes (I was a Physics major, for what that's worth). When you're ready to run your scientific computing codes on a supercomputer cluster, you'd usually rewrite it in C++ or Fortran (my research group used the latter), but to develop and debug at a small scale, you'd usually use Matlab, although the younger people like me might use Numpy, and there were one or two people who used Mathematica even for numerical computing (as opposed to symbolic algebra, which everybody used Mathematica for). It was around the time I was in university that Python really matured for numerical computing, but professors (as opposed to grad students) were likely to be already familiar with Matlab, so there wasn't much reason for them to learn Python. Andrew Ng was already a mid-career researcher when he made his course, which was probably based on older materials (I also learned basic neural networks in my numerical computing class in 2008), so it made sense for him to continue to use Matlab, especially because Octave exists as an open-source reimplementation of the basic functionality. These days, you wouldn't use anything else but Python for ML, at least until you really productionize the implementation at a large scale, at which case you might rewrite in C++ or Rust (I don't know if they even bother rewriting these days when most of the computation happens in GPUs or TPUs). And it's my understanding, although I'm not really too familiar these days, that Matlab has mostly pivoted into providing a toolbox of all sorts of esoteric numerical methods for engineering-related tasks like finite element analysis, as well as hardware simulation (using Simulink).

rg111 4y ago

I did everything in Octave. And it was a great learning experience. Octave is very easy to learn if you have previous programming experience. You won't _write_ programs a lot. There will be cookie-cutter code, and you will fill in some blanks. A line here a line there. Trust me, Octave wasn’t a deal-breaker if you tried. And a lot of formulae were the code.