MIT 6.S191 (2018): Deep Generative Modeling

[@weekoo9189]

Thanks for the Videos! really appreciated! I hope you upload more of the kinds

[@chaitanya.teja.g]

I expected Ian Goodfellow to deliver this lecture.

[@bayesianlee6447]

Of course it's difficult. generative model in deep learning world is somehow hyper level.
VAE and GAN, those two concepts are almost most important concepts on DL world. So, Don't be shameful or hate yourself when u having trouble to understand all.
Btw, taking course by Aaron free and in cozy home is quite lucky stuff. Thank you a lot

[@skipthis1142]

Actually the speaker doesn't communicate the information very well. He needs some "public speaking" training. He seems to know the information very well, just his communication isn't great. He should probably read his own transcripts to start.

[@rezar.tabrizi2812]

first lecture was awesome, next ones was good or ok ... this one is hard to understand!!!

[@skipthis1142]

Don't worry, it's not you. It's the speaker.

[@pranavmadanahalli5735]

ua-cam.com/video/Ly3GAnq2p34/v-deo.html
Same course but Fall 2017 semester.

[@binyuwang6563]

Are there some typo errors in ppts about posterior and inference model? (16:49)

[@bahmanahmadi1952]

this lecture needs some knowledge about fundamental matters before watching.for example maximum likelihood, Bayesian and prior probability distribution, and posterior estimation and divergence and.....

[@liberator48]

I'm curious if all those mathematical formulas actually make any sense to anyone... i mean, come on.

[@solidsinek14]

Greeks probably see something like aufjeodhbxısk
(because its their alphabet) ΣφγπΩψλ

[@liangli6276]

a little diffcult

[@mostinho7]

A little? I didn’t understand anything. I understood the first lecture fairly well