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Ask HN: Daily practices for building AI/ML skills?

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Re: Ask HN: Daily practices for building AI/ML skills?

#31

Post by pknerd »

zmgsabst wrote: post #29
pknerd wrote: post #27

Pardon me for hijacking this post but my question is something similar: What should be the roadmap as a developer to get into the GenerativeAI/LLM space? I want to learn how to use different LLMs, how to use them from hugging face and their different features like embeddings etc. I am a Python developer who has never worked on ML/data science before, I am mostly into Data Engineering

Are you trying to learn how train LLMs or use LLMs to produce things?

Sorry! Just updated my comment. I was talking about usage to build products

Re: Ask HN: Daily practices for building AI/ML skills?

#32

Post by wanderingmind »

DeathArrow wrote: post #21
janalsncm wrote: post #18

I got a masters degree in ML at a good school. I will say there’s pretty much nothing they taught me that I couldn’t have learned myself. That said, school focused my attention in ways I wouldn’t have alone, and provided pressure to keep going. The single thing which I learned the most from was implementing a paper. Lectures and textbooks to me are just words. I understand them in the abstract but learning by doing g…

ML is so much more than just neural networks. I would start by taking a free university level course in statistics. Then I would continue with the basics: SVM, linear regression, naive Bayes, gradient boosting, neural nets etc. I would not only train and fine tune them, but I would also build simple ones myself instead of just using libraries. Then I would continue to what you said, participate in Kaggle competitions…

This type of bottom up approach is terrible idea for a fast moving area like ML. Ultimately to get a job and make money in the area, you need to solve customer problems, starting with libraries and fine tuning is what needs to happen first. However you should try to learn fundamentals as you go and when you get stuck. It will take a very long time if you have a full time job or a student studying something else and doesn't help to get a job

Re: Ask HN: Daily practices for building AI/ML skills?

#33

Post by viksit »

(Former AI researcher + current technical founder here)

I assume you’re talking about the latest advances and not just regression and PAC learning fundamentals. I don’t recommend following a linear path - there’s too many rabbit holes. Do 2 things - a course and a small course project. Keep it time bound and aim to finish no matter what. Do not dabble outside of this for a few weeks :)

Then find an interesting area of research, find their github and run that code. Find a way to improve it and/or use it in an app

Some ideas.

- do the fast.ai course (https://www.fast.ai/)

- read karpathy’s blog posts about how transformers/llms work (https://lilianweng.github.io/posts/2023-01-27-the-transforme... for an update)

- stanford cs231n on vision basics(https://cs231n.github.io/)

- cs234 language models (https://stanford-cs324.github.io/winter2022/)

Now, find a project you’d like to do.

eg: https://dangeng.github.io/visual_anagrams/

or any of the ones that are posted to hn every day.

(posted on phone in transit, excuse typos/formatting)

Re: Ask HN: Daily practices for building AI/ML skills?

#35

Post by maurits »

I've learned the most from implementing papers. And being stuck. But me is me.

Since you mention SE, I'd choose a mini project in an area you love. The tooling you will learn along the way.

An hour a day is paradoxically not nearly enough, yet also a serious time investment of your day.

Maybe start by asking what exactly you want to learn? Applying ML to a practical problem, in user app? The math? The ideas?

Re: Ask HN: Daily practices for building AI/ML skills?

#36

Post by zmgsabst »

pknerd wrote: post #31
zmgsabst wrote: post #29

Earlier quoted context omitted.

Are you trying to learn how train LLMs or use LLMs to produce things?

Sorry! Just updated my comment. I was talking about usage to build products

I’m not an expert, but I just picked a project and used the OpenAI API — but with a wrapper that should let me swap out backends if/when I get a computer with a nice GPU.

Python is great for mixing API calls, document formatting, and other data scraping.

For myself, the problem was finding something interesting to do — in my case, generating videos from basic prompts.

Re: Ask HN: Daily practices for building AI/ML skills?

#39

Post by tsurba »

wanderingmind wrote: post #32
DeathArrow wrote: post #21

Earlier quoted context omitted.

ML is so much more than just neural networks. I would start by taking a free university level course in statistics. Then I would continue with the basics: SVM, linear regression, naive Bayes, gradient boosting, neural nets etc. I would not only train and fine tune them, but I would also build simple ones myself instead of just using libraries. Then I would continue to what you said, participate in Kaggle competitions…

This type of bottom up approach is terrible idea for a fast moving area like ML. Ultimately to get a job and make money in the area, you need to solve customer problems, starting with libraries and fine tuning is what needs to happen first. However you should try to learn fundamentals as you go and when you get stuck. It will take a very long time if you have a full time job or a student studying something else and d…

Getting a job to make money and solve customer problems as fast as possible was not a stated goal by the OP.

Besides, you are also wrong, having good fundamentals in the maths will help you pick up new methods much faster as they pop up. And especially if you want to come up with new methods (as in research), there are no shortcuts.

Re: Ask HN: Daily practices for building AI/ML skills?

#40

Post by spaniard89277 »

janalsncm wrote: post #18

I got a masters degree in ML at a good school. I will say there’s pretty much nothing they taught me that I couldn’t have learned myself. That said, school focused my attention in ways I wouldn’t have alone, and provided pressure to keep going. The single thing which I learned the most from was implementing a paper. Lectures and textbooks to me are just words. I understand them in the abstract but learning by doing g…

I only have old hardware at home. How viable is to practice this stuff on my own projects (and I'd like to touch JS as much as possible, despite everyone being on python)
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