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Comment by mhh__ | Hacker News Reader

I feel like this is often a distinction between engineering and science books.

I'm used to reading books on physics where the authors (even the Russians) give a bit of background and (usually made up) history but when I go to read a book on something like Finite Element Analysis (For engineers) it feels like the author is literally just dumping his life's work into LaTeX without any thought beyond A->B.

Don't get me started on pages and pages of MATLAB or Fortran code without any indentation, comments or variable names longer than two characters. (This is why I believe writing algorithms in real programming languages is playing with fire in textbooks).

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Matlab by itself isn't the problem, it's just that a lot of professors write pretty terrible code in their textbooks. Python won't fix that. None of the mathematics, physics, or engineering texts had much history outside of some occasional excerpts. I'd like to see more of that though as it helps things click for me.

I think MATLAB is a little bit of a problem. Or at least, I want to kill myself whenever I have to use it. Python too although in more subtle ways (I like to abuse the type system, Python is just a hacked together pile of shit with tolerable syntax)

Physics textbooks tend to get "unique" when you get to topics like Quantum Field Theory. Basic Textbooks are usually fairly to the point.

"Advanced Engineering Mathematics" is a good book with a fair amount of history (and written by a mathematician so no Engineering-isms e.g. Notation recognizable to other human beings)

With Matlab, you can immediately create a Matrix and transpose it, find the inverse...etc. I think it is optimized really well for undergraduate excercises that are really simple (I have two numerical methods textbooks which use Matlab fine). I agree that anything more complex than a couple of functions and a loop is probably better off somewhere else in a lot of cases. With that being said, it has built-in support for GUIs, sparse matrices and other stuff which is a lot harder in C++, so easy to see why it is popular for academic and R&D type work. For a student, the commercial cost is only ~$30 or free at a lot of schools, so usually not a barrier.

You seem to not consider a major player in the field: Python. There's probably a reason Andrew Ng switched from Matlab to Python for teaching.

I literally mentioned Python in one of my above comments lol and it is my daily driver. Still, as an undergrad with zero programming experience, Matlab was very easy to use for the kind of things that undergrads do in engineering and physics (play with matrices, differential equations, make charts...etc). I would agree that machine learning is likely to be easier in Python, but then again, ML students already know how to code, understand OO, and other concepts. Matlab is popular where people are good at math, but have no clue what objects are.

These are issues that a good editing process would resolve. Unfortunately the market for advanced engineering textbooks is so small that it's tough to justify paying an experienced editor to work through multiple revisions.

That's true about physics! I wonder if there are other fields that are written in such casual style. Undergrad textbooks in math are also very dry affairs. David Mackay was an exception, but he is a physicist.

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