already felling in love with this professor and his classes...
ZiLi-hf
I have no words for the absolute brilliance of the professor. God Bless
NeverthelessFigher
if you find this lecture challenging, it might be because you forget some basic linear algebra. Don't be discouraged by the somewhat trivial algebraic calculation. the Prof does a very good job in explaining the intuition and statistical foundation for doing PCA. PCA is so commonly used in psychology studies, yet no one in the my Psy department seem to have a clue where PCA is coming from.
bowenzheng
extremely helpful with building the basics and then moving forward
gouravkarmakar
Gave me some insight, Thanks. I liked the part about how u^TSu is the variance of the X's along the u direction. Good to know for an alternative viewpoint to Singular value decomposition as a PCA.
linkmaster
I was forwarding like crazy until I hear something and was thinking "Damn not only the first minute without audio". Just to realise my sound was mute
vegeta
49 min in and still hoping he'll get to PCA soon hahaha... great lecture though
yasmineguemouria
A good opportunity to burn calories would be to wipe the blackboard properly.
tilohauke
Is the professor teaching PCA by writing on a cloudy/unrubbed blackboard with key concepts so that we extract the key features out of the entire volume and be able to identify the most significant ones? Is that why he is writing on a blackboard as this?
END-ch
nice example of seeing matrix in perspective of stat
김경환-pzc
H is a n by n matrix, and v is a d-element column vector. H can not multiply v
zhenhuahu
Great lecture. Thank so much Professor.
aungkyaw
wonderful teacher and everything. But what's with the horrible chalk rubbing.
shashanksharma
Absolutely precious! Excellent in explaining details! Thank you.
ahmadmousavi
Shouldn't the empirical covariance matrix be divided by n-1 and not n?
StatelessLiberty
how to proof that eigenvectors are coulums of projection matrix
MsKouider
In 1:08:10, those lambda's should not be eigen values of Sigma ? (or covariance matrix ?)
tomasjurica
Can anyone pls help me with how prof. Come up on the final result from multiplication of Hv?? Steps i am little bit confused
danishmahajan
The only bothersome thing in this video is the dirty is the blackboard.
huzefaghadiyali
horrible. Don't max out your volume. There's nothing till you get a huge surprise at 1:15.
One of the cameras is tracking the movement of the lecturer, and it makes me dizzy. The view of the blackboard is enough. Even in 2016, the camera man at OCW still can't master how to record good video lectures.
