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2103 Curated Machine Learning, Data Science, AI & LLMs Interview Questions
Answered To Get Your Next Six-Figure Job Offer
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👨‍💻 Having Full-Stack & Coding Interview? Check  FullStack.Cafe - 3877 Full-Stack, Coding & System Design Questions and AnswersHaving Full-Stack & Coding Interview? Check 👨‍💻 FullStack.Cafe - 3877 Full-Stack, Coding & System Design Questions and Answers

Top 41 NLP Interview Questions

Entry Junior Mid Senior Expert
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NLP Theoretical Questions
Q1:   

Why is text preprocessing done in NLP?

  
Add to PDF   Entry 
Q2:   

When would you use Stemming over Lemmatisation, and vice-versa?

  
Add to PDF   Junior 
Q3:   

What is the use of PoS (Part of Speech) tagging?

  
Add to PDF   Junior 
Q4:   

What are some of the advantages of using the Bag-of-Words to extract features?

  
Add to PDF   Junior 
Q5:   

What are the differences between TF-IDF and TF?

  
Add to PDF   Junior 
Q6:   

How can you evaluate the performance of Language Models?

  Related To: ChatGPT, Model Evaluation, LLMs
Add to PDF   Junior 
Q7:   

What is a One-Hot Vector? How can they be used in Natural Language Processing?

  
Add to PDF   Junior 
Q8:   

What is the difference between Lemmatisation and Stemming?

  
Add to PDF   Junior 
Q9:   

What are the different types of text Preprocessing?

  
Add to PDF   Junior 
Q10:   

What is Syntactic Analysis?

  
 Add to PDF   Mid 
Q11:   

What is BLEU?

  Related To: Neural Networks
 Add to PDF   Mid 
Q12:   

What are some ambiguities faced in NLP?

  
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Q13:   

What is Latent Semantic Analysis?

  
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Q14:   

What is BLEU?

  
 Add to PDF   Mid 
Q15:   

Explain what is ROUGE?

  
 Add to PDF   Mid 
Q16:   

Why would you use Encoder-Decoder RNNs vs plain sequence-to-sequence RNNs for automatic translation?

  Related To: LLMs, RNN, Neural Networks
 Add to PDF   Mid 
Q17:   

What's the difference between Stateful RNN vs Stateless RNN? What are their pros and cons?

  Related To: RNN, Neural Networks
 Add to PDF   Mid 
Q18:   

How does ChatGPT understand context?

  Related To: ChatGPT, LLMs
 Add to PDF   Mid 
Q19:   

How is the Transformer Network better than CNNs and RNNs?

  Related To: CNN, LLMs, RNN
 Add to PDF   Mid 
Q20:   

Could you name some applications of the transformer network?

  Related To: ChatGPT, LLMs
 Add to PDF   Mid 
Q21:   

What's the difference between GPT vs BERT vs T5?

  Related To: ChatGPT, LLMs
 Add to PDF   Mid 
Q22:   

What methods to perform Feature Engineering from text data do you know?

  Related To: LLMOps, Feature Engineering
 Add to PDF   Mid 
Q23:   

What is ROUGE?

  Related To: Neural Networks
 Add to PDF   Mid 
Q24:   

What is Named Entity Recognition (NER)?

  
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Q25:   

What are some advantages of using TF-IDF over TF?

  
 Add to PDF   Mid 
Q26:   

What are some disadvantages of using a One-Hot Vector for Natural Language Processing?

  
 Add to PDF   Mid 
Q27:   

What loss function would you use for Sentiment Analysis?

  
 Add to PDF   Mid 
Q28:   

Name some types of Text Summarisation

  
 Add to PDF   Mid 
Q29:   

How has Translation of words improved from the Traditional methods?

  Related To: Feature Engineering, Neural Networks
 Add to PDF   Mid 
Q30:   

What are the uses of using RNN in NLP?

  Related To: RNN, Neural Networks
 Add to PDF   Mid 
Q31:   

What are the uses of LSTM in NLP?

  Related To: Neural Networks
 Add to PDF   Mid 
Q32:   

How is Convolutional Neural Networks (CNN) used in NLP?

  Related To: CNN, LLMs, Neural Networks
 Add to PDF   Mid 
Q33:   

What is intuition behind using CNN for NLP?

  Related To: CNN, Neural Networks
 Add to PDF   Senior 
Q34:   

What causes the accuracy of Sentiment Analysis to be low?

  
 Add to PDF   Senior 
Q35:   

How would you create a Neural Captioning Model?

  Related To: Neural Networks
 Add to PDF   Senior 
Q36:   

What are some of the differences between NLP and CUI (Conversational User Interface)?

  
 Add to PDF   Senior 
Q37:   

Explain the concept behind the Neural Machine Translator

  Related To: Neural Networks
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Q38:   

What is Semantic Analysis?

  
 Add to PDF   Senior 
Q39:   

What is an Embedding in NLP?

  Related To: Neural Networks
 Add to PDF   Senior 
Q40:   

When and where to use Attention Mechanisms in Language Models?

  
 Add to PDF   Senior 
Q41:   

What's the importance and the difference of monitoring Generative models with Reference Text vs without Reference Text?

  Related To: LLMOps, LLMs
 Add to PDF   Senior 
 
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Optimization algorithms are extensively used in training machine learning models. Data engineers employ algorithms like gradient descent, stochastic gradient descent, and variants (e.g., Adam, RMSprop) to optimize the model parameters and minimize th...
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