Unit #7 Lesson 3: Kernel estimation

This video is about Unit #7 Lesson 3: Kernel estimation

[Nana-wufb]

Thank you so much Brian, this is super helpful!!!!

[wryltxw]

Is it possible to get a playlist to reflect the sequence of the videos in the series. Makes it easier to download the entire series in one step.

[kaiwan]

Thank you for this great video. The references are very helpful.

[satyamgopal]

Thanks Brian for informative video. Is there a way to apply differentiation post smoothing..?

[mbikaziketelo]

this is for me but I am understanding you . thank you

[summadayze]

I think Epenechnikov kernel should be in form of (a+bx^2). you accidentally put the square outside the brackets

[rolfjohansen]

Let's say you were given a task : Make me the MLE (Maximum Likelihood Est) of:
Y=f(xi) + ei (as presented in the vid)
and they do not specify any kernel or how the f(xi) looks like.
How to attack this?

[areejareej]

Is kernel regression is another name of kernel ridge regression?

[Mohammed-ylwr]

is not the Epanechnikov kernel defined as 3/4 (1 - x^2) not 3/4 (1-x)^2

[lucga]

At the beginning of the video, you define that the variance is constant for all e_i. Worse in the example you give, it is clear that the variance is not constant