In case you missed it(it was on the frontpage here a couple of days ago), play around with this awesome 3D visualisation and animation to get a basic understanding: https://bbycroft.net/llm
This is so cool, thanks for sharing.
Ask HN: Daily practices for building AI/ML skills?
51–60 of 135 posts
Re: Ask HN: Daily practices for building AI/ML skills?
#52Earlier 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…
The better your skillset, the highly sought after you are and harder to replace. And that translates in more money, if money are your sole motivation.
Re: Ask HN: Daily practices for building AI/ML skills?
#53Roughly speaking, the roadmap for a typical ML/AI student looks like this: 0) Learn the pre-requisites of math, CS, etc. That usually means calc 1-3, linear algebra, probability and statistics, fundamental cs topics like programming, OOP, data structures and algorithms, etc. 1) Elementary machine learning course, which covers all the classic methods. 2) Deep Learning, which covers the fundamental parts of DL. Note, t…
As someone a wee bit along the journey but with the maths dragging me down a bit, I've found that, while in a perfect world I'd love to get my maths up to solid 2nd year undergrad level, it's just going to take me another year or so. That hasn't stopped me moving forwards. I understand y = ax + b, bits of linear algebra, gradient descent, but I still don't have the critical intuition to pass a college level maths exam.
This has helped me build the intuition for understanding these concepts in ML, and as an experienced developer I've found I've been able to pick up the ML stuff relatively easily - it's mostly libraries at the practical level. This has in turn shown me two things: ML is data quality, prep, and monitoring; I actually like the maths: it annoys me that there's this whole branch of knowledge that I don't grok intuitively and I want to know more. As I go deeper on the maths, I find myself retrospectively contextualising my ML knowledge.
So: do both and they'll reinforce each other - just accept you'll be lost for a bit.
Also: working with LLMs is incredible, as you can skip the training step and go straight to using the models. They're fucking wild technology.
Re: Ask HN: Daily practices for building AI/ML skills?
#54Earlier quoted context omitted.
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.
They made a reasonable assumption. Abstraction helps you to be productive. It's certainly good to understand everything all the way down to the actual physics behind computing, but its not necessary especially at the start. I don't have to know exactly how logic gates work to program in JS and make a difference. I assume the same applies to ML. Motivation is what prevents most people from learning difficult to learn…
>I don't have to know exactly how logic gates work to program in JS and make a difference.
I don't regard time spent in University to learn how logical gates work and many other useful things, as a loss of time. And, as a web developer/architect (after many other industries I worked in), I typically make more money than peers who don't. And knowing how things work, helped me immensely in my career. Not everything is solvable by looking on Stack Overflow.
It depends on what professional level you are content with.
Learning was not only motivated by money - for me- I was genuinely curious about computers and software since I was a kid.
Re: Ask HN: Daily practices for building AI/ML skills?
#55Earlier 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…
OP did not state that getting an ML job was a goal.
I for one would be interested in learning more foundational stuff; I have no interest (though perhaps that process would change this!) in a particularly ML job, and certainly not in learning how to point and click and run other people's work from a YouTube video with a scream-face thumbnail.
For those who feel similarly, I asked about it recently, maybe something you like the look of:
https://news.ycombinator.com/item?id=38320244
I also came across (doesn't seem it was mentioned there) Understanding Deep Learning (Simon Prince) which looks like it might be good:
https://mitpress.mit.edu/9780262048644/understanding-deep-le...
Re: Ask HN: Daily practices for building AI/ML skills?
#56Earlier quoted context omitted.
With 2015 Macbook, I do not have such luxury
Does it not run Python? I’m working off a 4GiB system with no dedicated GPU — and the Python APIs for OpenAI work fine, but admittedly, I have a Linux system.
I was talking about other LLMs, do they also provide API? What LLM are you using for image generation?
Re: Ask HN: Daily practices for building AI/ML skills?
#57Earlier 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…
Strong agree
Re: Ask HN: Daily practices for building AI/ML skills?
#58I 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…
As Andrej Karpathy says, understanding it deeply is required to take your skills to the next level and not make mistakes. As a practice, one should implement their own neutral net and manual backprop to start their understanding.
Re: Ask HN: Daily practices for building AI/ML skills?
#59(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 o…
Would recommend Zero to Hero by Karpathy as well
Re: Ask HN: Daily practices for building AI/ML skills?
#60I'd start by replacing "1 hour daily" with "4 uninterrupted hours every weekend". 1 hour is not enough for a focused deep dive into anything.