May i know what is the de-separation property you're talking about? I don't quite follow when u say "conditioning this...this is the tail...it has to go through this...so scratch this part out" Please advise in this regards.
Can you explain why you are summing (at 2:15)? It seems to me that it should be a product there, not a sum. How did you come out with that formula for p(z_k, x_1:k)? Thanks.
@srinathsvce. D-separation was covered under Graphical models. Look through the play list. Chapter 13.x
mailvishalshekhar 1 month ago in playlist Machine Learning
Thanks a lot for posting such informative videos.
May i know what is the de-separation property you're talking about? I don't quite follow when u say "conditioning this...this is the tail...it has to go through this...so scratch this part out" Please advise in this regards.
srinathsvce 1 month ago
Can you explain why you are summing (at 2:15)? It seems to me that it should be a product there, not a sum. How did you come out with that formula for p(z_k, x_1:k)? Thanks.
barabum2 7 months ago
@barabum2 I'm using the property that for any random variables X and Y, if Y is discrete then p(x) = sum_y p(x,y).
In the video, (Z_k,X_{1:k}) is playing the role of X, and Z_{k-1} is playing the role of Y.
mathematicalmonk 7 months ago
Your good teaching addicted me to go forward seeing more videos
Good that you described everything slowly in details, Bad that you described everything slowly in details ;)
amirkhalili82 7 months ago