u/Stunning_Meringue_47

Same as above.

Hey! I am interested in edge compute and would like to hear yall's thoughts on TinyML running this fall. I've heard the labs are essentially just changing one line of python and the prior lectures are available online so it there any worth in signing up for it or should I just take it on my own time.

P.S. Reddit Mods - This info is not available online I already checked + I want to garner more informaiton.

I know someone is gonna say, "JuSt LoOk at OtHeR Posts" but there no good info yet. Has anyone taken this? Whats the best way to prepare.

I've heard 6.3100 is pretty easy, would it be better to take 16.30? Are there any other control theory classes people would recommend?

Interested in feedback on Deep Learning and Grad ML. Which class is more useful/challenging/better to take?

Hey all, current course 6 sophomore broadly interested in signal processing, ML, and hardware. I'm currently looking for some class reqs for next fall.

I really enjoyed 6.1210, in particular how it challenged me to think about problems rather than memorize problem solving techniques. After a semester of hardware specific classes (6.191, 6.200), I'm encouraged to take another algorithms class. Two classes that caught my eye next semester were 6.1220 and 6.7810. I've heard varying things about the two, mostly that 6.1220 may not be that useful, and by the description of 6.7810, there seems to be some overlap with past ML classes Ive taken, although I've heard its very difficult. I guess I'm not worried about how useful a class is, but more about the intuition and skills it develops.

Is there anything to say about Deep Learning, Grad ML, or TinyML?

I'm pretty excited to take 6.2050 with Steinmeyer in the fall. 6.601 also caught my eye, I was wondering if there were any thoughts about this class in regards to difficulty/relevance.

Any other recommendations?

-Thanks