NLP interview questions.
A curated set of 18 questions that repeatedly exercise NLP concepts in AI/ML interviews.
How is BERT different from GPT?GenAI & LLM · medium · Evidence 88/100Implement Byte Pair Encoding.ML Coding & PyTorch · hard · Evidence 77/100Design entity matching across different Alexa skills.ML System Design · hard · Evidence 77/100Explain core NLP and deep-learning concepts used in an Alexa system.GenAI & LLM · medium · Evidence 77/100Explain core NLP modeling choices.GenAI & LLM · medium · Evidence 75/100Explain BERT and its pretraining objectives.GenAI & LLM · medium · Evidence 75/100Explain Transformers in an NLP context.GenAI & LLM · medium · Evidence 75/100Explain an NLP project and its modeling choices.Project & Behavioral · medium · Evidence 75/100Explain embeddings, tokenization, attention, and BERTGenAI & LLM · medium · Evidence 41/100How do tokenization choices affect professional-domain text?GenAI & LLM · medium · Evidence 41/100BERT: Architecture and TrainingML Fundamentals · medium · Evidence 41/100When would BERT be overkill compared with a simpler embedding model?GenAI & LLM · medium · Evidence 41/100When would you choose topic modeling instead of generic clustering?ML Fundamentals · medium · Evidence 41/100Embeddings for Retrieval vs Token EmbeddingsGenAI & LLM · medium · Evidence 41/100Tokenization TradeoffsML Fundamentals · medium · Evidence 41/100How would you choose a loss function for a speech or language-modeling task?ML Fundamentals · hard · Evidence 41/100Explain tokenization choices for an LLMGenAI & LLM · medium · Evidence 40/100What Is an LLM?GenAI & LLM · easy · Evidence 34/100