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 understandable given how the close to the bleeding edge this new version is...
Perhaps an even better complement was Karpathy's famous course[2] - similar material but builds towards GPT instead of SD. The fastai coding style is somewhat esoteric (to me) so it was helpful to contrast with Karpathy's more familiar style. I recommend doing both courses. Also I believe the fastai folks are planning a part 3 which covers LLMs; looking forward to that.
Concepts from part 2 helped my hobby project, a 7-day forecast of renewable electricity and power price[3].
Feels pretty great to have built my own Stable Diffusion and GPT! I am grateful to Jeremy and Andrej.
Depends. Some would benefit from simultaneous, others sequential. I did them in "chunks" starting with fastai but that was more driven by the release schedule. Personally I'd recommend trying both and seeing which style you prefer, focus on whichever one makes your more excited to get your hands dirty and play with stuff.
I didn't really track... apparently there's 30-ish hours of video, but lectures are just the beginning. The real learning happens when you play and build. The first lesson was released in October I think.
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 understandable given how the close to the bleeding edge this new version is...
Perhaps an even better complement was Karpathy's famous course[2] - similar material but builds towards GPT instead of SD. The fastai coding style is somewhat esoteric (to me) so it was helpful to contrast with Karpathy's more familiar style. I recommend doing both courses. Also I believe the fastai folks are planning a part 3 which covers LLMs; looking forward to that.
Concepts from part 2 helped my hobby project, a 7-day forecast of renewable electricity and power price[3].
Feels pretty great to have built my own Stable Diffusion and GPT! I am grateful to Jeremy and Andrej.
[1] https://course19.fast.ai/part2
[2] https://karpathy.ai/zero-to-hero.html
[3] https://greenforecast.au/