Summer-Analytics-2022
This repository contains the course notes, implementations of various ML models and Hackathon submission notebooks of Summer Analytics program.
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L1 and L2 Regularization (Part 2 of Notes)
READ FROM THESE LINKS. (Specially first one)
A linear regression model that implements L1 norm for regularisation is called lasso regression, and one that implements (squared) L2 norm for regularisation is called ridge regression. To implement these two, note that the linear regression model stays the same,
but it is the calculation of the loss function that includes these regularisation terms.
It is possible to combine L1 and L2 regularization, which is also known as Elastc Net Regularization.
Link for further reading: LINK