And how do you know if someone’s eligible for security clearance without applying for it? (Other than the obvious “be a US citizen, don’t be a spy” part.)
It kind of bothers me that the parent and other readers here are passing off knowing linear algebra as some kind of esoteric skill. Linear algebra is a year 2 course in a undergraduate eduation. There are polished libraries to make it fast.
Unless you mean enough knowledge to be writing linear algebra libraries, there is no need to consider this skill a high hurdle.
But most people that have any exposure to it can pick it back up fairly rapidly. And most people that have a reasonable exposure to math in general could probably come up to speed (a little less) rapidly.
From what I’ve seen, the year 2 course is great for graphics programming, game development, that sort of thing. It’s not enough for the tasks that require more serious linear algebra, when you’re working with systems of linear equations, large matrices, etc. These “big” linear algebra problems come up a lot in fields like physics simulation, finance, and machine learning / AI.
I’ve done some hobby work in graphics and game development, and I’ve done some professional work in physics simulation. The kind of linear algebra you use in physics simulation is a different beast.
That it's a year-2 undergraduate course for some people argues more for forgetting than remembering it, if you're not using it regularly.
I can easily imagine that an overly aggressive linear algebra requirement will eliminate many excellent candidates.
Linear algebra wasn't a requirement. I took it as an elective just for my own curiosity. I have a feeling loads of programmers really don't know anything about linear algebra, and probably a large number are like me and learned it due to interest in game development.
You can assume they're interested in esoterics like those who can grasp the spherical harmonic equations used to model the daily magnetic flux epoch models to control sats via mag torque, those who can do a multivariate 512 dimensional SVD reduction against pipelined multi spectral data to create sharpened images, create fuel optimal paths in constrained resource starved environments while dodging projected debris paths, .. you know, all that jazz.
I took through calc 3 + discrete math, but didn’t have to take the full linear algebra course for the BS in CS. I’m sure I could refresh myself on calculus, but almost no one is regularly maintaining their more advanced math knowledge in this field.
It's unclear what "linear algebra" means to GP, though. I agree writing linear algebra libraries is next level, since that involves numerical code and knowing FP math well.
Umm, not in Pennsylvania government high schools, not typically. Not by a long shot.
Given that is the case, to answer your question: yes, linear algebra is the foundation of ML. No, a lot of impactful day-to-day ML engineering can be done without touching linear algebra.
This is how assembly is the basis of compilation and programming. But you probably are going to get a whole lot of work done without ever using it.
It's generally a nice flex when applicants can code assembly, and usually a yellow-flag when the company suggests they require knowledge of assembly.
To me, my eyebrows raise when an industry person mentions linear algebra. I'm just saying the odds are really low that you actually use it.
That's either a wishful thinking or a stretch of definitions, IMHO.
The short answer is "You can't, not with 100% certainty.".
Based on my experience from decades ago, the long answer is "Anyone who's a US citizen and doesn't lie about their drug use and debts can get a Secret clearance.". Things MIGHT have significantly changed since my clearance lapsed way back when, but I doubt it.
That is, eligibility concerns whether or not the State Department will consider your application, not whether or not they will grant the clearance after performing their background and lifestyle investigation.
