Basic Inference in Bayesian Networks

This video shows the basis of bayesian inference when the conditional probability tables is known. Approximate inference will be coming up.

[@andresrosso]

Excelent, but the solutions was not shown

[@mozark24]

Around 10:30. In the 4th statement where b=t, a=f, e=f, why are you using a=t in the last 2 probabilities instead of a=f? You kind of skimmed that part too quickly

[@ghadialhajj]

You are right, it should be a=f in both probabilities

[@srijan4622]

I was stuck in that part for a while as well.

[@yoyo987987]

Thanks for the video! I was actually looking for the choice of relevant variables which you clarified in this video! Great!

[@Dr.hayder374]

How can i calculate p(A|B, c) in table? I mean what process of calculate that

[@stanleysmall1947]

Terrific explanation.

[@MubashirullahD]

That solves one question from my assignment :)

[@roeybh]

Well explained! thanks

[@ohmster123]

Thank you! Helped me a lot.

[@akshatjain7742]

Really well explained!

[@xingjianwang1894]

Really clear~ like it.

[@thexxmaster]

i love you, thanks heaps

[@PepekBezlepek]

P E R F E C T, I FINALLY understood this!