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Deep Learning Foundations to Stable Diffusion

course.fast.ai

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Re: Deep Learning Foundations to Stable Diffusion

#51

Post by jph00 »

frabia wrote: post #44
jph00 wrote: post #4

Hi folks. Nice to see our new free (and ad-free) course here on HN! This course is for folks that are already comfortable training neural nets and understand the basic ideas of SGD, cross-entropy, embeddings, etc. It will help you both understand these foundations more deeply, since you'll be creating everything from scratch (i.e. from only Python and its standard library), and to understand modern generative modelin…

Maybe odd question, but: would you recommend taking this course if my goal is to build (and sell) products leveraging ML? (e.g. SaaS) As in, with the pace of improvements from other AI startups and general availability of their APIs (e.g. GPT-4), is there a specific advantage (aside from maybe cost) to learning to build my own models? Or is the course more suitable for people wanting to become ML engineers (or simila…

Part 1 would probably be best for that: https://course.fast.ai . Lots of alums have gone on to do what you describe -- it's probably a good idea to have the level of understanding introduced there even if you mainly use external APIs. Part 2 is more for folks who want to go deeper in order to try new research ideas, optimize their models beyond standard approaches, etc.

Re: Deep Learning Foundations to Stable Diffusion

#52

Post by _giorgio_ »

stevesimmons wrote: post #35
crakenzak wrote: post #33

Earlier quoted context omitted.

Is there any chance that the transcripts can be published on the website? I'd love to be able to search through them. love the course btw!

This would be ideal. I much prefer seeing everything in text form, in the same place, without having to jump out to YouTube. I can read many times faster than listen, and more easily skim back if I realise I don't understand something.

Good luck with the code.

Re: Deep Learning Foundations to Stable Diffusion

#53

Post by jph00 »

amelius wrote: post #49

How much math does the reader need under their belt? Is high-school math sufficient?

Yes high school math is sufficient, as long as you did basic calculus (derivatives and the chain rule) and probability. We cover stuff that's well beyond high school math, but it's introduced when it's used, and we link to external resources for more details as needed.

Re: Deep Learning Foundations to Stable Diffusion

#54

Post by jph00 »

_giorgio_ wrote: post #47

Why would I want to learn fast.ai... I feel that while this course is surely superb, I don't want to invest time in a new framwework. What's your opinion? We've got lightning, fast.ai, and another one that I forgot about... why?

This course doesn't use the fastai framework.

But to answer your question -- the reason IMO to learn the fastai framework (or indeed any software which incorporates a significant amount of novel research) would be to learn about the new ideas that it introduces, in order to become a more effective and informed practitioner. And if you find you like it, you may even decide to use it.

Re: Deep Learning Foundations to Stable Diffusion

#55

Post by thelittleone »

jstx1 wrote: post #13
nbzso wrote: post #10

This is cool, but I have a fundamental question. Why learn machine learning when all the machines will learn how to create and control themselves and powerful elites will offload the burden of governments to control us? Or we race ourselves to fulfill the last jobs on earth? Is this progress for humanity or enslavement and the end of our species? I am serious. This question is honest. Maybe my IQ is too low to unders…

This question isn't specific to machine learning - if you've given up already, don't bother learning anything and see how it goes.

He didn't say or imply he had given up and I found the question quite interesting.

Re: Deep Learning Foundations to Stable Diffusion

#56

Post by andy_ppp »

This looks awesome, however I probably need to do a bootcamp with real people to compete and have comradery with to actually retrain on the basics in this.

It doesn't matter where in the world this is (I like to travel), but does anyone have a recommendation for in person bootcamps on AI?

Re: Deep Learning Foundations to Stable Diffusion

#57

Post by hoseja »

mattyyeung wrote: post #29

I just finished this! My thoughts: I recommend it. I feel I can now read an arbitrary paper, frown a lot, and eventually understand what it's talking about - to the point where I can implement my own buggy version. And hey, I built my own stable diffusion!! I found the previous version of this course[1] to be a good complement: it's older (predates SD) but I feel it explains core concepts slightly better. Very unders…

How long did it take you?

Re: Deep Learning Foundations to Stable Diffusion

#58

Post by bravura »

frabia wrote: post #44
jph00 wrote: post #4

Hi folks. Nice to see our new free (and ad-free) course here on HN! This course is for folks that are already comfortable training neural nets and understand the basic ideas of SGD, cross-entropy, embeddings, etc. It will help you both understand these foundations more deeply, since you'll be creating everything from scratch (i.e. from only Python and its standard library), and to understand modern generative modelin…

Maybe odd question, but: would you recommend taking this course if my goal is to build (and sell) products leveraging ML? (e.g. SaaS) As in, with the pace of improvements from other AI startups and general availability of their APIs (e.g. GPT-4), is there a specific advantage (aside from maybe cost) to learning to build my own models? Or is the course more suitable for people wanting to become ML engineers (or simila…

Just my two cents, as someone with 8000 academic citations and one AI SaaS exit, on AI entrepreneurship:

The more time you spend on marketing, the better.

We found that as our AI got worse, our product got better.

Re: Deep Learning Foundations to Stable Diffusion

#60

Post by _giorgio_ »

jph00 wrote: post #4

Hi folks. Nice to see our new free (and ad-free) course here on HN! This course is for folks that are already comfortable training neural nets and understand the basic ideas of SGD, cross-entropy, embeddings, etc. It will help you both understand these foundations more deeply, since you'll be creating everything from scratch (i.e. from only Python and its standard library), and to understand modern generative modelin…

I hope that one day you will do another part about LLM, in pytorch, that would be great :-)

Thanks for this material.

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