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Do not respond to maleposters. See Rule 7.

Anonymous

Should I take a class on Fourier analysis or nonlinear / discrete optimization? Which one would be more useful for reinforcement learning / control theory type applications?

Anonymous

Sorry for posting a very specific question as a new thread.

More broadly if you girls wanna discuss machine learning related topics let's use this thread for that. Does anyone else here study machine learning or control topics in university?

More broadly if you girls wanna discuss machine learning related topics let's use this thread for that. Does anyone else here study machine learning or control topics in university?

Anonymous

Fourier analysis is going to be very useful anytime you're dealing with image, sound, or any time of signal.

Discrete optimization, I've never really felt the need for a course. Convex optimization definitely get at least a primer on though.

But do whatever feels the most fun to you Anon. None of these topics are anything you can't learn later.

t. ML engineer, ex math PhD student

Discrete optimization, I've never really felt the need for a course. Convex optimization definitely get at least a primer on though.

But do whatever feels the most fun to you Anon. None of these topics are anything you can't learn later.

t. ML engineer, ex math PhD student

Anonymous

>>119485

From a purely mathematical standpoint, Fourier analysis; it's beautiful. From a machine learning perspective, I'd probably say discrete optimisation (but I have no idea what content your course is offering).

From a purely mathematical standpoint, Fourier analysis; it's beautiful. From a machine learning perspective, I'd probably say discrete optimisation (but I have no idea what content your course is offering).

Anonymous