So You Wanna Be an ML Engineer

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So you wanna be a machine learning engineer.

Well, here’s just some of the math you’re gonna need: you’re gonna need linear algebra to represent data and model transformations, you need probability and statistics to reason about uncertainty and learn things from the data, like get your machine to learn things.

And the way that the machine learns things, well, you’re gonna need multi-variable calculus to understand gradients and the way that models are trained.

See, what you have to remember about these technical careers is that the really exciting stuff, the stuff that makes you feel alive like, holy crap, it did this?

I wrote a program to do that? I built a model that can do this?

All this exciting stuff sits on top of this huge stack of math.

I mean, if you wanna really build stuff yourself and extend it, really understand what’s going on well enough to extend it in super interesting and novel ways, you gotta know the math.

It’s more than just importing some- somebody else’s API.

Ultimately, if you wanna do novel things and, and provide it to everybody, you gotta know what you’re doing at a fundamental level because all that math is very hierarchical and if you wanna get to that top, you gotta build the foundation first.

Further reading: What Math To Learn for Skill Stacking .

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