Is every neural network a deep-learning model?
Neural networks can have different depths. Deep learning generally refers to networks with multiple learned layers, although there is no single universally applied minimum depth.
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It can, especially when adapting a pretrained model. However, limited task-specific data can still cause overfitting, so careful evaluation and simpler baselines remain useful.
No. Performance depends on the data and task. Simpler models can outperform deep networks, particularly when structured data is limited or the problem has simple relationships.
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