The best explanation I found on this topic. No fancy equations, or formulas; a very intuitive approach to the plot. This video deserves much more views Keep up the good work!
@andreitrofin50992 жыл бұрын
This is a great explanation of how kde bivariate plots works. Intuitively, you can guess what the figure tells you, but this video tells why so nicely!
@abhilashgeesala3723 жыл бұрын
Loved the video and your intonation as you speak.
@snesh932 жыл бұрын
Is it possible to get the information on the contour area ? What I mean is after computing the probability density function of a 2D gaussian distribution, the hill will be in the third dimension, Can I get the values of the projection of this (till 3 sigma values of the variables) ?
@iftikhar36092 жыл бұрын
Amazing !!!
@BlueSkyGoldSun2 жыл бұрын
Where I can find tutorial about PMF
@tompower40084 жыл бұрын
The explanation makes sense! However, do you have any idea how to implement a Contour pdf? You just explained a simple statement for 8:37!
@AppliedAICourse4 жыл бұрын
In most instances, you need not implement the underlying code behind the jointplot function which plots a contour plot. But, in case you are curious about how it's actually implemented, here is one of the simple ways to do it. Take various 2D points(with x and y coordinates) and compute the z (the density) at each of these 2D points.. Now join the 2D points which have the same value of z into a line and color it with darkness proportional to the value of density (z).
@KLCSSrasthi Жыл бұрын
@@AppliedAICourse what is that full code ..I mean after kind=kd what you have written?
@suryakantismce5 жыл бұрын
Hey, great video! Can you share the ipynb that you used? Thanks.
@sashibezawada32395 жыл бұрын
Cheating :( You never got to plotting a 3 variable or 4 variable PDF