Question:

Which of the following scenarios might necessitate using a deep $($many layers$)$ neural network instead of a shallow $($few layers$)$ one?

Options:

Tasks with a large number of features and complex relationship

Simple linear regression problems

Complex tasks with hierarchical features, such as image or speech recognition

Situations where computational resources are very limited

Problems where interpretability of the model is crucial