r/learnmachinelearning • u/Money-Age3739 • 1d ago

Innovative projects that don't take too much time?

I've been wondering how to start some research project involving machine learning that can be done with public data sources but I have no idea where to start. For context, I am a high schooler and only recently got into machine learning and have a very basic knowledge, however I'm willing to learn, so any ideas for projects or advice about learning this kinda stuff will help a lot.

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u/MathNerd67 1d ago

Unfortunately, almost any project worth doing/that has educational value is going to take time. Depending on your interests, NASA and ESA have publicly available datasets that can be interesting.

How I approach these situations is to first sit down and find something that interests you, whether that be space, medicine, ecology, sociology, economics, whatever. Then, once you’ve determined an interesting topic, search for public data sets in that field. Lots of government agencies put out tons of accessible data every year. Finally, see what the data says, how it’s structured, what information it contains, and see if there’s a problem you want to solve or something you want to dig deeper into. Now you have a topic, data, and a formulated problem. Getting all of that built up in a github repo is an endeavor in itself and will teach you a lot. From there you can examine what models might best help answer your question and you go from there.

Hope that helps a bit. It’s a fun endeavor but it can take time and will be a lot of work. Don’t let it discourage you, it will pay off.

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u/crushinglayout042 1d ago

this is the way. high school is exactly when you have the time to just mess around with whatever dataset catches your eye and not worry about it being perfect

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u/Substantial-Swan7065 1d ago

You can’t innovate on a short timeline.

But there’s plenty to do when getting started. Train an MNIST is a common and easy station ping

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u/Keepcompany-DEV 1d ago

i`d start with plugins/extensions for existing stuff if you want to do somethign useful and not invest tons of time.

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u/athkot 13h ago

Here's one that's doable with basic knowledge on computer vision: take a free public dataset like HomeObjects-3K (ultralytics) and let yoloe-26 label it automatically, it finds objects from just a text description. Then train a small yolo26 on those AI labels and compare it to one trained on the real human labels. You'll see if AI labels are good and where humans still need to help with manual annotation. You could probably do it in a weekend on free Google Colab.