Natural Language Processing (NLP) Interview Questions

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Natural Language Processing (NLP) is one of the most sought-after machine learning skills with applications across a variety of business domains. The state of art and application in NLP has benefitted immensely from the exponential progress within the space of deep learning. If you are interviewing for a NLP position then expect lots of questions from the deep learning space. In this post, I am enumerating some popular questions specifically focussed on NLP that may help with your interview preparations. Happy practicing!!

1. What is a word embedding?
2. What all word embedding you are aware of?
3. Describe the approach used by word2vec to create word embedding.
4. Describe the approach used by Glove for creating word embedding?
5. When will you use Glove vs Word2Vec? For example consider summarization and classification problem What is negative sampling in Word2Vec
6. What is vanishing gradient problem in training neural networks? What is the impact of vanishing and exploding gradients on RNNs?
7. How do LSTM and GRU address the vanishing gradient problem?
8. How will you use convolution for natural language processing?
9. What are transformers?
10. What is multi headed attention?
11. What is fine tuning in BERT?
12. Design a classifier for Named Entity Recognition
13. Design a classifier for relationship extraction