Lesson 10: Deep Learning Foundations to Stable Diffusion, 2022

[@fabriai]

Jeremy Howard, what you're doing to help people understand these models is priceless. Thank you, thank you, thank you. God bless you.

[@tokosby9700]

Nnnn

[@sunderrajan6172]

Great Lectures as always Jeremy! Its been a while since Lesson 10, I am eagerly waiting for remaining lessons.Thanks!

[@jordankuzmanovik5297]

Any news?

[@KellyNicholes]

I haven't delved into the juicy bits of python for over ten years now, and watching this was making me feel "home" again. I'm so thirsty for more! Added bonus: You learn how to create your own Stable Diffusion model from scratch. I can hardly wait.

[@sunderrajan6172]

Remaining lessons have been posted in the last two weeks. I am really excited and the lessons are awesome as always from Jeremy.

[@timandersen8030]

Thanks for the video lectures! It's really cool that you start out introducing an awesome application first (i.e. Stable Diffusion) and how it works before teaching the foundation and starting back from there.

[@howardjeremyp]

Glad you like them!

[@sandeepm625]

Great content and awesome teaching style. Towards the end you touched upon matrix and vectors and the APL language . Languages like Octave and Matlab also provide vector or matrix operation as part of the language .

[@tsenguun]

Looking forward to the next lesson

[@baaaaayesian]

Thank you for the videos Jeremy. I appreciate it so much!

[@ItzGanked]

jupyter also has documentation for python and other libraries inside the notebook if you go to help python reference. Keeps you inside of the notebook instead of searching the web and will provide docs for the version of python you are using.

[@jesse-mikael]

For the clip image text embeddings would it be possible to use a pretrained language model to first get the text embeddings and then use those as the targets for image embeddings in a traditional optimisation loop? Also thank you for these lessons I am deeply grateful

[@derekcarday]

Jeremy, where is the best place to stay updated on papers? I'd like to read all the trending papers as they come out.

[@CoolDude911]

It could be that the Markov way of modelling the problem stops you getting into local optimums or images which are not really part of the target distribution. The model has to "change course" between iterations. I remember generating a picture of a seal with a head coming out of each end of the seal. At some point the model was not sure about where the head of the seal was but had to commit to one decision or another.

[@heejuneAhn]

Do we use same Random noise in each step or sampling every time in each step.

[@tsenguun]

Still waiting for the full course

[@vivekakaviv]

Thank you.

[@satirthapaulshyam7769]

41:00

[@bilalch83]

Sensei Jeremy Howard

[@mattkkma]

For those looking for Jonathan Whitaker paper walkthrough kzbin.info/www/bejne/kInYfGl_h6-fpM0