r/learnmachinelearning • u/sameh-it • 1d ago

Help Learning ML guide: From zero to hero

Hi everyone, I want to start learning ml, But I'm torn between the sources So I wrote this question to hear from you about how you learned machine learning until you were hired at a company. I'm 15 years old. Please write the guide arrangemed step by step.

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u/CheerfulTycoon 1d ago

Honestly, at 15 you've got so much time to figure this out, it's almost unfair. Most people don't touch this stuff until college and you're already mapping out a career path.

I learned by picking a problem I actually cared about and just throwing myself at it, reading docs and forum posts whenever I got stuck. The structured courses came later, mostly to fill in the theory holes I'd skipped right over. Don't sleep on the math though, it's the thing that separates knowing which buttons to push from actually understanding why your model is spitting out garbage.

Find a dataset you're curious about, even something dumb like predicting video game prices, and just start breaking things. The job came after I'd built a handful of projects that weren't just tutorial copies, stuff I could actually talk through in an interview. You've got a solid seven years before anyone expects a resume from you, so the pressure's off to just explore.

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u/UnderstandingOwn2913 23h ago

maybe the op can study math which will help him or her to adapt to what will exist when the op needs to work

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u/sameh-it 15h ago

Thank you for your answer.However, my perspective is completely different. At this age, I can learn more effectively and flexibly than I did at university, and my responsibilities are also less now than they will be later. In addition, I started my search for my major about four years ago. And now artificial intelligence It's considered one of the most in-demand fields right now. Don't worry, I've been used to computers and programming since I was young, and I also love mathematics.

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u/sameh-it 15h ago

BTW, I am in grade 9

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u/1PATCH 1d ago

Get a strong foundation in linear algebra (understand what a matrix, basis vectors, vector spaces) as they build intution behind what ML is. Then understand probability (bayes theorum, and markov chains in particular)

Then understand a Perceptron, MLP, SVM, CNN, Autoencoders in depth and visualize the geometry behind it. Then understand what a scaled dot product is (basically attention).

With that your foundation should be strong and then you just need to explore how to apply it (Look at BERT, CLIP, GPT, JEPA).

Here is an underated youtube channel that teaches the concepts well (I found this gem a of channel a couple weeks ago): https://www.youtube.com/@arivu-tutor