1. What typically causes underfitting in a machine learning model?
2. Which of the following is not a key method of regularization?
3. What is a common effect of applying regularization on a neural network's training and validation loss?
4. What does Batch Normalization achieve that is similar to the effects of traditional regularization methods?
5. Where is Batch Normalization typically applied in a layer sequence?
6. How does L1 regularization affect a model's weights?
7. In the context of regularization, what is the purpose of the λ parameter?