@kimzauto5045
Clearly one of the best videos on the topic, the use of examples was really good.
@AK47dev1_YT
فوق العاده بود آقای امینی
@vinodpareek2268
You are one of the best teacher i have ever seen..
@nosachamos
Fantastic, very clear and concise. Great work!
@davidsasu8251
I love you guys!
@ahmarhussain8720
very good way of explaining
@romesh58
Great video. The whole series is very good
@scottterry2606
Outstanding. Thank you.
@hullopes
It was very clear and helpful.
@shambles7409
in 34:35 how do I calculate the log-likelihood of the action given the state?
@hanimahdi7244
Thank you!
@mehwishqazi4381
Very well explained. How to get the slides? The link in the bio mentions coming soon!
@Lezmonify
Is there a typo at 10:01? Intuitively, it seems like the exponent of γ should (i - t) since, in current formulation, the reward terms will quickly go to 0 when t becomes large.
@vincentkaruri2393
This is really good. Thank you!
@sitrakaforler8696
Dude it's awesome T^T
@waqasaps
wow, thanks.
@ycnim34
Thank you all for these great videos. One thing I want to mention is that the audio volume is a little bit too low
@niazmorshedulhaque4519
Excellent tutorial indeed
@Inviaz
What is max Q (s' , a' ) ? When i have a lot of future states and they are unknown , how can I destinate the max Q ( s' , a' ) ? 24:00
@mmattb