Interview SkillsNLP

What is tokenization? What is TF-IDF? What are word embeddings? What is attention? How do you evaluate NLP models? What does bidirectionality add in a Bi-LSTM text classifier? What is multi-head attention and why is it better than single-head? You fine-tuned BERT for sarcasm detection. What layers did you modify? How does Word2Vec differ from contextual embeddings like BERT? Why did NLP need embeddings in the first place? How are word embeddings actually trained, and why do they end up meaningful? How does Word2Vec learn word vectors — what's the difference between CBOW and Skip-gram? What was ELMo, and why was it an important step toward modern LLMs?

NLP Interview Questions

Text processing, language representation, attention, and evaluation for NLP interviews.

13 questionsskill

What is tokenization? →