Data Science, Machine Learning, Linear Regression, Ridge Regression, Lasso Regression.
Overfitting: The regularization term in Lasso Regression discourages the model from fitting the training data too closely, thus helping prevent overfitting. It encourages the model to be simpler and more generalizable. Handling Multicollinearity: Lasso can handle multicollinearity between features