Lasso (l1) and Ridge (l2) Regularization Techniques

What is the need for Ridge and Lasso Regression? When we create our linear model with the best-fitted line and come on testing phase then because of increased variation, our model is over-fitted, So It will not work well in the future also not provide appropriate accuracy. Therefore, to reduce overfitting, ridge and lasso regression came into the picture. Both are powerful techniques with a slight difference used for creating such models that are efficient and computationally fit to reduce over-fitting. It is a process to classify the classes and provide additional information to prevent over-fitting.