The annotated PyTorch training loop
idlemachines.co.uk
The annotated PyTorch training loop
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Re: The annotated PyTorch training loop
#2https://idlemachines.co.uk/courses/foundations doesn't render correctly on mobile
Re: The annotated PyTorch training loop
#3https://idlemachines.co.uk/courses/foundations doesn't render correctly on mobile
even the submitted page doesn't, huge margin if you zoom out on mobile (Firefox)
Re: The annotated PyTorch training loop
#4The host website seems extremely interesting in general. Anyone here used it before?
Re: The annotated PyTorch training loop
#5The host website seems extremely interesting in general. Anyone here used it before?
The design is similar to what Claude generates. Makes me skeptical that all the content is AI-generated.
Re: The annotated PyTorch training loop
#6The host website seems extremely interesting in general. Anyone here used it before?
The design is similar to what Claude generates. Makes me skeptical that all the content is AI-generated.
This looks better than 90% of websites I visited. The palette is pleasant, content has the right density and spacing is very relaxed. If this is AI-generated without some clever prompt tuning, frontend as a profession is done.
Re: The annotated PyTorch training loop
#7PyTorch already does a huge job at keeping DL not verbose. It captures the complexity to allow you to make a whole GPT model with it, running on your GPU, and keep the code readable. Yes, there are a lot of breaking points, but at some point, DL is supposed to be non trivial, it handles math concepts most people don’t understand. That is why Data Scientists have a job ;)
Re: The annotated PyTorch training loop
#8https://idlemachines.co.uk/courses/foundations doesn't render correctly on mobile
even the submitted page doesn't, huge margin if you zoom out on mobile (Firefox)
I've seen that huge margin when zooming out issue before. I'm using Safari on iOS, but have also experienced this issue in Chrome on Android. It's probably some sort of weird compatibility thing for desktop websites. You start zoomed correctly, but for some reason, there's horizontal scroll and you can also zoom out. For seemingly no reason, as I doubt any of the websites where this happens intended it.
Note that I can't reproduce it myself on this submission, but I've seen it so many times and in so many different places that I don't think it's a website issue.
Re: The annotated PyTorch training loop
#9Earlier quoted context omitted.
The design is similar to what Claude generates. Makes me skeptical that all the content is AI-generated.
This looks better than 90% of websites I visited. The palette is pleasant, content has the right density and spacing is very relaxed. If this is AI-generated without some clever prompt tuning, frontend as a profession is done.
I am 95% sure Claude came up with the design. It has all the tell-tale signs like the all-caps bold letter-spaced microcopy (See the orange "Sharpen your AI fundamentals" on the landing page.) Many card-like elements with a colored border on one side only. The italic serif font as subtitle. Etc. That being said I'm not judging. It's competently done.
I also put the content of a workshop into an LLM detector and it said 100% of the text was likely AI generated.
I'd just like the author to disclose how much of the content is entirely LLM-generated.
Re: The annotated PyTorch training loop
#10PyTorch already does a huge job at keeping DL not verbose. It captures the complexity to allow you to make a whole GPT model with it, running on your GPU, and keep the code readable. Yes, there are a lot of breaking points, but at some point, DL is supposed to be non trivial, it handles math concepts most people don’t understand. That is why Data Scientists have a job ;)
I mean partial derivatives aren't that complicated if you know normal derivatives, which most people do. And backpropagation isn't too difficult either.
The value of PyTorch lies more in utilizing accelerators like GPUs while offering a nice abstraction. But you can build your own (inefficient) tensor library without too much effort as e.g. Andrej Karpathy has shown in his "NN zero to hero" youtube series.