Interview SkillsDeep Learning

What is backpropagation? Why do neural networks need activation functions? What is dropout? What is a CNN? What is vanishing gradient? Walk me through backpropagation from scratch. What is vanishing gradient and how does LSTM solve it? Explain the Transformer architecture from scratch. How does BERT differ from GPT in architecture and pretraining? Pretraining vs fine-tuning vs prompt-based learning — differences? How do token embeddings combine with positional embeddings in a Transformer? Batch normalization vs layer normalization — which is preferred in Transformers? Explain dropout — training vs inference behavior. What is softmax and what does temperature do to it? Encoder-only vs decoder-only vs encoder-decoder Transformers?

Deep Learning Interview Questions

Neural network fundamentals for modern ML and AI engineering interviews.

15 questionsskill

What is backpropagation? →