Lesson 11 2022: Deep Learning Foundations to Stable Diffusion

[@YippiekayyaiMF]

Thank you Jeremy for all the contributions you have made and for democratising the knowledge to public domain

[@carlaluoja8402]

Great style of teaching! Really cracking deep into the stuff, but also keeping it fun and light. Thank you Jeremy!

[@kawalier1]

You,re really a Code Artist. Very like your approach to see big picture :)

[@sandeepm625]

Excellent teaching. Really helped me understand the stable diffusion model. As a request, could also provide similar training for GAN style models like VQGan or StyleGAN?

[@akhileshpandey123]

Thanks for the course. Very different from any other course I have done.. Will complete this one..

[@alinour7488]

You do not know how long I've have been waiting for this course, Thank you so much!

[@cristian-bull]

14 videos at once. Jesus... guess holy week vacations are cancelled.

[@quansumonner]

God is back with a new course :)

[@godiswatching_895]

Any chance you can change the timestamp to "Homework" 55:43 - 57:00 instead of "Experiments and benchmarks". Amazing video as usual of course.

[@gennarofarina94]

From kzbin.info/www/bejne/ipeQaXlrpp2Lrdksi=_E-KtZmXlqsFfgXy&t=1255 to 21:09 I have spit out my lungs by laughing. Thanks for this part, one of the most useful of the entire course. 💪

[@yufengchen4944]

RReally? another 10 videos about Stable diffusion?!

[@xNWDD]

The timing of this was the second best timing possible for me (the first one would have been when recorded), thank you for making this openly available.

[@howardjeremyp]

You're so welcome!

[@jonathangrant7788]

I see you went over numba for faster operations, do you plan on teaching cython or pybind11 or codon? That can move the needle even more

[@pranavdeshpande4942]

I think the paper should've just said "MSE".

[@Poppik81]

E is not the expected value, but ELBO, the evidence lower bound.

[@mkamp]

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