Lasso Vs Ridge Regression| L1 & L2 Regularization
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Lasso and Ridge regression are regularization techniques used to prevent overfitting. Also called as L1 and L2 regularization techniques, which basically make use of L1 and L2 penalty.
In this video i cover everything you need to know about them. I address important data science interview questions as well like:
1)How do lasso and ridgre regression work?
2)When should you use L1 regularization and when L2 regularization?
3) Which technique is preferred for feature selection and why?