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This course together with the new fastai ones [1] seem to be exactly what I was looking for. The micrograd video is excellent. [1] https://course.fast.ai
Hopefully, I'll manage to get further with this course.
Anybody tried the lessons in an Apple MBA/MBP M1/M2? Is it easily applicable?
I'm doing an ML apprenticeship [1] these weeks and Karpathy's videos are part of it. We've been deep down into them. I found them excellent. All concepts he illustrates are crystal clear in his mind (even though they are complicated concepts themselves) and that shows in his explanations. Also, the way he builds up everything is magnificent. Starting from basic python classes, to derivatives and gradient descent, to…
Do you run the code as you watch? I’ve been simply watching them on a palm from a hammock and I’m worried I’m not getting the full experience.
Watching only is much nicer for entertainment.
Wonderful! Just went through the GPT video the other day and it was great. Andrej has a talent for pedagogy via simplification.
He is a master educator. While at Stanford he developed their undergrad machine learning intro course named cs231n which immediately became legendary. It's somewhat out of date on some details but it's still well worth watching especially as delivered by Andrej. You can find all 11 lectures on YouTube.
Earlier quoted context omitted.
Approximately 40 cents USD for 15 minutes from cursory research.
I'm completely unfamiliar with this market. Do you rent these on AWS? Or where?
My hive mind connection must be good because I literally finished this course yesterday. It was very satisfying to learn how transformers worked, to finally be able to turn the obscure glyphs of the research papers into real code, but I think transformers are too big for what I can do on my own computer. The author mentioned that the toy transformer he was building in the final video took 15 minutes to train on his A…
With the original hyperparameters, it was 30-60 minutes, with a pruned down network and adjusted hyperparameters, about 6 minutes, and a variety of optimizations beyond that to bring it down.
If you want the nano-GPT basically feature-identical (but pruned down) version, 0.0.0 at ~6 minutes or so is your best bet.
You can get A100s cheaply and securely through Colab or LambdaLabs.
I'm doing an ML apprenticeship [1] these weeks and Karpathy's videos are part of it. We've been deep down into them. I found them excellent. All concepts he illustrates are crystal clear in his mind (even though they are complicated concepts themselves) and that shows in his explanations. Also, the way he builds up everything is magnificent. Starting from basic python classes, to derivatives and gradient descent, to…
My email address is first part of my username (before the “-“) at blueheart dot io.
Anybody tried the lessons in an Apple MBA/MBP M1/M2? Is it easily applicable?
It should be completely fine, you don't really need a GPU to do this course. Maybe the exercises right at the end you won't get good performance, but the exact performance isn't all that important.