Deep Learning & Architectures

Summary

Expect questions on how CNNs, RNNs and Transformers work, why attention replaced recurrence, and practical debugging of training issues (vanishing gradients, overfitting).

• 1Be able to explain backpropagation and attention from first principles, not just at a high level.
• 2Practice explaining why Transformers largely replaced RNNs for sequence tasks.
• 3Review common training failure modes and how you'd diagnose them.