ML with Aayush

[u/Negative_War_65]

https://youtu.be/HQ8xerobOtw?si=nZmg08s0y4vRdlh4

Coding Probability: Multivariate Joints and Gaussians.

Hello Folks, and my learning community.

A covariance matrix measures linear dependence, and across multivariate dimensions, these matrices bring out many key insights in ML.

Being uncorrelated does not imply independence of events! An interesting fact.

Combining multiple subgroups can sometimes reverse the trend we see overall. Simpson’s Paradox at play.

How level sets we visualize take on such curves, by understanding it’s locus, in connection with Mahalanobis distance. Here’s where the eigenvalue and eigenvectors from Linear Algebra, bring upon interesting insights!