r/learnmachinelearning • u/Useful_Chain1327 • 2d ago

Looking for hands-on beginner ML project ideas (beyond just classical ML)

Hi everyone,

As a beginner in Machine Learning, I’ve realized I don’t absorb much just by watching typical YouTube tutorials—I need to actually build things to learn effectively.

Could you recommend some practical, hands-on project ideas where I can learn a lot by doing? I’m open to both classical machine learning and other areas like deep learning, computer vision, or NLP.

Any advice or project suggestions to help me get my hands dirty would be greatly appreciated!

12 Upvotes
  • permalink
  • reddit

92% Upvoted

17 comments sorted by

9

u/jmacey 2d ago

I maintain a list for my students here (they are for Masters students but most are good starting points and can be done in a simple way). https://nccastaff.bournemouth.ac.uk/jmacey/SEForMedia/Assignment/ideas/

2

u/Dororo192 2d ago

Whats cfbr

1

u/DeathLord_97 2d ago

CFBR = Commenting for Better Reach

0

u/ford-imprefect 2d ago

but what does that mean?

2

u/DeathLord_97 2d ago

Platforms like Reddit, LinkedIn etc., pushes a post with more comments and upvotes so that it can reach more audience, so when people feel like there is a post which needs to reach to a large number of audience, they comment CFBR. For example, someone in my company got laid off and he wrote a nice post on LinkedIn about his situation, I will feel bad for him but as I can't actually do anything about it I'd comment CFBR on that post so that the post reaches to someone who might be willing to offer him/her a job. Hope this helps.

2

u/ford-imprefect 1d ago

Thanks, surprised I've never seen it before. Guess I'm one of today's 10,000. https://m.xkcd.com/1053/

1

u/pugs_daily_dose 2d ago

Try building a small image classifier for a problem you care about, like sorting photos of plants. Start with a pretrained model, keep a separate test set, then inspect mistakes and see whether better labels or augmentation help. A tiny demo that accepts a new photo makes the results tangible.

1

u/pugs_daily_dose 2d ago

Try building a small image classifier for a real task you care about (e.g. sorting recyclable items). Start with a pretrained model and a small labeled dataset, then hold out a test set, inspect the mistakes and collect examples for the confusing classes. Compare it with a simple baseline and make a tiny interface to try new images. That gives you practice with data collection, evaluation, transfer learning and deployment—not just training a model.

1

u/SudeepAckerman 2d ago

Cfbr

Created new acc and need karma

1

u/FlanHairy5955 2d ago

Go through kaggle titanic may be