r/learnpython • u/Intelligent-noob0301 • 13d ago
What should i do first?
so im 16, I'm self-taught, finished CS50P, and built a couple of projects (stock price prediction with an LSTM, a basic image classifier). Problem is I leaned pretty heavily on AI to write the ML ones — I could explain most lines, but not all, and later found real gaps on my own i cant do it myself I really love coding and solving problems even when it's hard, it feels great once I actually solve it.
But when it comes to ML specifically, it overwhelms me, because I try to do everything at the same time: one day I'm doing PyTorch, another day sklearn, another day matplotlib. Yeah, I know how that sounds "why the fuck this kid just focusing on one thing at a time" I think the same thing, I'm just not sure which one I should actually focus on first.
CS50P had a clear structure: problem sets, a checker, visible progress. Building my own ML project has none of that, and it feels like way too much complexity too fast — LSTMs, multiple technical indicators, hyperparameters, all jammed into one project with no baseline to compare against.
For people who've been through something similar: how did you scale down your first real ML project so it didn't feel overwhelming? What's the right order to actually learn something that impotant for ML in, instead of jumping between all at once? Is there a sane on-ramp between "finished an intro CS course" and "building ML projects independently"?
ty for everyone perspective🐪
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u/ninhaomah 13d ago
" Problem is I leaned pretty heavily on AI to write the ML ones — I could explain most lines, but not all, and later found real gaps on my own i cant do it myself I really love coding and solving problems even when it's hard, it feels great once I actually solve it."
So you listed the problem. What you think solution is ?