Describe overfitting and L1/L2 regularization

Explain what overfitting means in machine learning and why it causes problems. Then describe L1 and L2 regularization:

• How each one changes the loss function.
• The qualitative effect of each (for example, sparsity or weight shrinkage).
• How they help reduce overfitting and when you might choose one over the other. Overview: This question tests understanding of model generalization and regularization techniques by asking about overfitting and L1/L2 regularization and how they affect model parameters.