Multivariate probability density, contour plot EDA Lecture 14@Applied AI Course

#ArtificialIntelligence,#MachineLearning,#DeepLearning,#DataScience,#NLP,#AI,#ML

[@shivamtyagi5783]

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!

[@andreitrofin5099]

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!

[@abhilashgeesala372]

Loved the video and your intonation as you speak.

[@snesh93]

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) ?

[@iftikhar3609]

Amazing !!!

[@BlueSkyGoldSun]

Where I can find tutorial about PMF

[@tompower4008]

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!

[@AppliedAICourse]

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]

​@@AppliedAICourse what is that full code ..I mean after kind=kd what you have written?

[@suryakantismce]

Hey, great video! Can you share the ipynb that you used? Thanks.

[@sashibezawada3239]

Cheating :( You never got to plotting a 3 variable or 4 variable PDF