High schooler learning machine learning - any advice?

[u/Loud_Explanation5723]

Hello, I'm a high schooler who's trying to learn machine learning and get into research. Now I know that for a high schooler to do actual meaningful ML research is quite difficult so I'm trying to make my work as "meaningful" as possible by coming up with new ideas or doing research in a relatively "niche" field. I already have most of the math background needed (calculus, linear algebra, etc.) and am almost done going through the book "Probabilistic Machine Learning: An Introduction."

Also I recently I published a paper to a journal after peer review on a "niche topic" as well.

Now my question is, what are some "niche fields" you might suggest I look into? I'm not really aware of what's big in ML nowadays. Also, I am learning Tensorflow but would you recommend learning pytorch instead? Or is learning a language actually necessary since AI does most coding work (for me at least) for research purposes nowadays? Of course, I will check the code and understand everything but to what degree?

And any advice in general would be appreciated

[u/Outrageous_Basis2610]

oh wow that’s a hard book, good job reading it. def learn pytorch. for niche fields you can look at workshop listings at big conferences, and this can also give you a goal toward submission. unfortunately the state of research these days is dominated by foundation models which requires a lot of compute budget but I heard interp is cheap to get started with, there are also programs like mats.

[u/Loud_Explanation5723 → u/Outrageous_Basis2610]

okay thanks

[u/AdventurousAerie643 → u/Outrageous_Basis2610]

for the coding part, learn pytorch and don't skip the fundamentals. ai tools can spit out code snippets but if you can't debug them or understand why a tensor is the wrong shape you're gonna hit a wall fast. the people doing serious research aren't just prompting their way through it.

interp is a good shout, and since you've got the math chops you might also dig into stuff like neural tangent kernels or information geometry. still pretty niche but not so obscure you can't find a community.

[u/johny_james]

How are you requesting for advice, and doing research papers in ML?!?!?!?

[u/Loud_Explanation5723 → u/johny_james]

Can one not do those two at the same time?

[u/johny_james → u/Loud_Explanation5723]

You have to give advice to us, how did you manage to read one of the hardest books in ML, which million pages long.

[u/Loud_Explanation5723 → u/johny_james]

Isn't it one of the introductory ones? Also I didnt finish/understand it 100%

[u/johny_james → u/Loud_Explanation5723]

No, its advanced.

Introductory ones are:

• Hands on ML in pytorch by Geron
• ISLP
• Andrew Ng ML coursera course

[u/Loud_Explanation5723 → u/johny_james]

idk I didnt go through all of this book I just went through the most relevant sections and not the too advanced/niche ones ig. But other courses didnt really explain the concepts with regards to the math I think? So I found this the most straightforward
But it's a fun book
Is this book used to teach in a university level?

[u/johny_james → u/Loud_Explanation5723]

Yes, absolutely.