2 years? Sheesh. This is the type of stuff that makes me think genuis is a biological thing.
In the UK, 3 years is common.
Just know stuff (or, how to achieve success in a machine learning PhD)
41–50 of 108 posts
Re: Just know stuff (or, how to achieve success in a machine learning PhD)
#42If anyone's reading over this and feels "Gosh, I'll never be an ML dev; this is way too much": I don't know most of that list, and still manage to be a productive researcher. I learn what I need as I go. That's probably the optimal strategy. I'm skeptical of first-principles learning. It's great to immerse yourself in theory, but when you've gone all the way to "topology" you've probably gone beyond the limit of what…
The author and you seem to be talking to different audiences, you're talking about ML eng and OP is talking about ML researchers. Researchers absolutely need to know a lot, not necessarily all the way to topology or w/e but definitely the underlying mathematical principles in order to advance the field (IMO).
I'm an ML researcher, and I'm with sillysaurusx on this. I actually know most of the things on the list, but only because my research is mainly in model compression and computational efficiency. Recently I've been interested in adapting diffusion models to generate music (in raw audio domain), and I'd say only 5 out of 18 bullet points in ML section are relevant - the rest falls from "nice to know" to "irrelevant".
Re: Just know stuff (or, how to achieve success in a machine learning PhD)
#43The problem with this list, although impressive in scope, is that it is not clear how /deeply/ one should know each of those items on the list.
One can write several papers for each one of those items on list.
Knowing the concept well enough to pass a job interview is a much lower bar than well enough to innovate and push new knowledge.
Re: Just know stuff (or, how to achieve success in a machine learning PhD)
#442 years? Sheesh. This is the type of stuff that makes me think genuis is a biological thing.
I was about to comment on the short PhD in "2-and-a-bit years" -- and how the UK expectation for PhD program duration is so different from in the US.
And it wasn't to say that he's a genius. It's that the program is planned to be shorter, and in fact, there's less funding available to go longer even if you wanted to.
Re: Just know stuff (or, how to achieve success in a machine learning PhD)
#45Earlier quoted context omitted.
Now is a terrible time to start a PhD in ML. If you do a CS PhD, pick literally any other subfield.
Sounds a lot like my dad telling me to go to law school instead of getting into cs. He thought the ultimate goal of cs is to make everyone in the field obsolete... well maybe he was right in the end.
Lawyers too (maybe they are first)
Re: Just know stuff (or, how to achieve success in a machine learning PhD)
#46Good references seem to be missing.
Re: Just know stuff (or, how to achieve success in a machine learning PhD)
#472 years? Sheesh. This is the type of stuff that makes me think genuis is a biological thing.
> 2 years?
Half of the items, and almost all in the "Mathematics" section, you would have learned during your BSc/MSc (if it's in applied math or physics, and Python programming is your hobby). I can't find the author's CV, but there is 5 years from him returning his MSc thesis in 2017 to returning PhD thesis in 2022. Maybe he studied ML for all those 5 years, or maybe he took off 2 years to travel the world, who knows.
Re: Just know stuff (or, how to achieve success in a machine learning PhD)
#48The tone of the post is pretty off putting. It reads as a "look how smart I am!" article - the author doesn't even pretend to be modest.
Should they be? In this case wouldnt it end up being false modesty?
Like, if this person cant say "Look at me, I am UNUSUALLY INTELLIGENT!" then who can?!
Re: Just know stuff (or, how to achieve success in a machine learning PhD)
#49Good references seem to be missing.
Agreed that it would be nice, but exactly how much of the work of becoming educated are you willing to ask this person to do on your behalf?
Re: Just know stuff (or, how to achieve success in a machine learning PhD)
#50"The stuff is what the stuff is, brother." --from a James Mickens talk on machine learning, https://www.youtube.com/watch?v=ajGX7odA87k&t=13m40s
Can confirm, the way ML is used in many businesses is like an egg drop: You open up Jupyter, load in some data, and play around with various models until you find one that fits the data, then use it to try to predict future data. If the future results comport with the model, congratulations: your egg is safe, at least for drops of that height.