Machine Learning | Ridge Regression-L2

1. 1Apply L2 Regularization to a Linear Regression model to reduce overfitting
2. 2Use Ridge Regression to analyze data with multiple features
3. 3Compare the performance of Ridge Regression with other regularization techniques
4. 4Configure the alpha parameter in Ridge Regression to optimize model performance
5. 5Test the model on a dataset to evaluate its effectiveness

Data scientists and machine learning engineers can benefit from understanding Ridge Regression to improve model performance and reduce overfitting

💡 Ridge Regression with L2 Regularization reduces overfitting by adding a penalty term to the loss function

Reduce overfitting in Linear Regression with Ridge Regression & L2 Regularization!