> the time I spent learning Octave/Matlab for Andrew Ng's course was 100% wasted time

Really?

If you have programming experience, you don't really need to learn Octave.

Some formulae were the code.

In case of others, the whole program was written, with one or two missing lines that you had to implement.

I spent zero time learning Octave, because there was nothing to learn.

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?

> Does Python handle matrix math as well?

If you're playing around interactively, it's a bit easier to write (in Matlab)

    m = [1 0 0 ; 0 0 -1 ; 0 1 0]

than (in Python)

    m = np.array([[1, 0, 0], [0, 0, -1], [0, 1, 0]])

Also a bit longer example:

    m = rand(3,4)
    a = [0.1 0.2 0.3]
    m \ a'

versus

    m = np.random.rand(3,4)
    a = np.array([0.1, 0.2, 0.3])
    np.linalg.lstsq(m, a.T)
    wtf?
    google...
    fine!
    a = np.array([[0.1, 0.2, 0.3]])
    np.linalg.lstsq(m, a.T)

But if you're developing software, you can't really easily and reliably deploy Matlab or Octave to run in the cloud in your production systems, whereas Python you can.

Matrix math in python is a bit clunkier, because matrices are not native to the language. That said, numpy, the standard for matrix math in python, is quite nice. Its documentation is, imo, miles ahead of matlab's and the APIs are a bit more sane.

This brings up a good point. If the goal is to understand the underlying concepts, it's quite possible Octave is a better tool. Matrix math is fairly clunky in any mainstream programming language.

MATLAB is still in heavy use in physics, mainly for experiments bc of simulink and the control systems toolbox

When I worked on the GPS III program back in the day, my job largely consisted of translating scientists' Matlab script into Ada.

Now there's an app for that https://www.adacore.com/qgen :)

I hate MATLAB with a burning passion, but Simulink is a damn good piece of software.

It's fairly common I have a little dataset I need to do some fft's on and draw a graph or some other similar one-off task. MATLAB still wins for getting the job done.

I wish someone would make "MATLAB with all its toolboxes, but with python syntax, in a colab-like IDE".

Is that not what numpy/scipy with Jupyter (as well as the various distributions that package them) essentially provide? If you just want an all-in-one that has a supported Matlab FFI interface, there's Julia.

The amount of Octave needed for the class was manageable.

Learning Octave made me wish all languages supported matrices, vectors, and the necessary operations.