You are interviewing for a machine learning role. Answer the following core questions: 1. Explain the bias-variance decomposition of prediction error and how it relates to underfitting and overfitting. 2. Compare batch normalization and layer normalization: how each is computed, where each works well, and their trade-offs. 3. Explain why vanishing gradients happen in deep neural networks and describe practical ways to mitigate them.