@research-focus-group, now that we’ve worked on implementing a better method of calculating inverse, we’ll divert our efforts towards understanding and implementing regularization:
Regularization is important since it prevents overfitting of linear regression models in the face of large number of parameters. It is important to understand the properties of Lasso and Ridge as they are also interview favorite topics!