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Natural Language Processing (NLP) Interview Questions

This document provides a curated list of 100 NLP interview questions commonly asked in technical interviews. Covering topics from the fundamentals of text processing to deep learning–based language models, this list is updated frequently and is intended to serve as a comprehensive reference for interview preparation.

Sno Question Title Practice Links Companies Asking Difficulty Topics
1 What is Natural Language Processing? Analytics Vidhya NLP Basics Google, Facebook, Amazon Easy NLP Basics
2 Explain Tokenization. Towards Data Science – Tokenization Google, Amazon, Facebook Easy Preprocessing
3 What is Stop Word Removal and why is it important? TDS – Stop Words Google, Facebook, Amazon Easy Preprocessing
4 Explain Stemming. TDS – Stemming Google, Amazon, Microsoft Easy Preprocessing
5 Explain Lemmatization. Analytics Vidhya – Lemmatization Google, Facebook, Amazon Easy Preprocessing
6 What is the Bag-of-Words Model? TDS – Bag-of-Words Google, Facebook, Amazon Easy Text Representation
7 Explain TF-IDF and its applications. TDS – TF-IDF Google, Amazon, Microsoft Easy Feature Extraction
8 What are Word Embeddings? TDS – Word Embeddings Google, Facebook, Amazon Medium Embeddings
9 Explain the Word2Vec algorithm. TDS – Word2Vec Google, Amazon, Facebook Medium Embeddings
10 Explain GloVe embeddings. TDS – GloVe Google, Facebook, Amazon Medium Embeddings
11 What is FastText and how does it differ from Word2Vec? TDS – FastText Google, Facebook, Amazon Medium Embeddings
12 What is one-hot encoding in NLP? Analytics Vidhya – NLP Encoding Google, Amazon, Facebook Easy Text Representation
13 What is an n-gram Language Model? TDS – N-grams Google, Facebook, Amazon Medium Language Modeling
14 Explain Language Modeling. TDS – Language Modeling Google, Amazon, Microsoft Medium Language Modeling
15 How are Recurrent Neural Networks (RNNs) used in NLP? TDS – RNNs for NLP Google, Facebook, Amazon Medium Deep Learning, Sequence Models
16 Explain Long Short-Term Memory (LSTM) Networks in NLP. TDS – LSTM Google, Amazon, Facebook Medium Deep Learning, Sequence Models
17 What are Gated Recurrent Units (GRU) and their benefits? TDS – GRU Google, Facebook, Amazon Medium Deep Learning, Sequence Models
18 What is the Transformer architecture? TDS – Transformers Google, Facebook, Amazon Hard Deep Learning, Transformers
19 What is BERT and how does it work? TDS – BERT Google, Facebook, Amazon Hard Language Models, Transformers
20 What is GPT and what are its applications in NLP? TDS – GPT Google, Facebook, Amazon Hard Language Models, Transformers
21 Explain the Attention Mechanism in NLP. TDS – Attention Google, Amazon, Facebook Hard Deep Learning, Transformers
22 What is Self-Attention? TDS – Self-Attention Google, Facebook, Amazon Hard Deep Learning, Transformers
23 Explain Sequence-to-Sequence Models. TDS – Seq2Seq Google, Facebook, Amazon Medium Deep Learning, Generation
24 What is Machine Translation? TDS – Machine Translation Google, Amazon, Facebook Medium Applications
25 Explain Sentiment Analysis. Analytics Vidhya – Sentiment Analysis Google, Facebook, Amazon Easy Applications
26 What is Named Entity Recognition (NER)? TDS – NER Google, Amazon, Facebook Easy Applications
27 What is Part-of-Speech Tagging? TDS – POS Tagging Google, Facebook, Amazon Easy Linguistic Processing
28 Explain Dependency Parsing. TDS – Dependency Parsing Google, Amazon, Microsoft Medium Parsing
29 What is Constituency Parsing? TDS – Constituency Parsing Google, Facebook, Amazon Medium Parsing
30 Explain Semantic Role Labeling. TDS – Semantic Role Labeling Google, Amazon, Facebook Hard Parsing, Semantics
31 What is Text Classification? Analytics Vidhya – Text Classification Google, Facebook, Amazon Easy Applications
32 What is Topic Modeling? TDS – Topic Modeling Google, Amazon, Facebook Medium Unsupervised Learning
33 Explain Latent Dirichlet Allocation (LDA). TDS – LDA Google, Amazon, Facebook Medium Topic Modeling
34 Explain Latent Semantic Analysis (LSA). TDS – LSA Google, Facebook, Amazon Medium Topic Modeling
35 What is Text Summarization? Analytics Vidhya – Summarization Google, Facebook, Amazon Medium Applications
36 Differentiate between Extractive and Abstractive Summarization. TDS – Summarization Google, Amazon, Facebook Hard Applications
37 What are Language Generation Models? TDS – Language Generation Google, Facebook, Amazon Hard Generation
38 Explain Sequence Labeling. TDS – Sequence Labeling Google, Amazon, Facebook Medium Applications
39 What is a Conditional Random Field (CRF) in NLP? TDS – CRF Google, Facebook, Amazon Hard Sequence Modeling
40 What is Word Sense Disambiguation? TDS – WSD Google, Amazon, Facebook Hard Semantics
41 Explain the concept of Perplexity in Language Models. TDS – Perplexity Google, Facebook, Amazon Medium Language Modeling
42 What is Text Normalization? Analytics Vidhya – NLP Preprocessing Google, Amazon, Facebook Easy Preprocessing
43 What is Noise Removal in Text Processing? TDS – NLP Preprocessing Google, Facebook, Amazon Easy Preprocessing
44 Explain the importance of punctuation in NLP. TDS – NLP Basics Google, Amazon, Facebook Easy Preprocessing
45 What is Document Classification? Analytics Vidhya – Document Classification Google, Facebook, Amazon Easy Applications
46 Explain the Vector Space Model. TDS – Vector Space Google, Amazon, Facebook Medium Text Representation
47 What is Cosine Similarity in Text Analysis? TDS – Cosine Similarity Google, Facebook, Amazon Medium Similarity Measures
48 What is Semantic Similarity? TDS – Semantic Similarity Google, Amazon, Facebook Medium Semantics
49 What is Text Clustering? TDS – Text Clustering Google, Facebook, Amazon Medium Unsupervised Learning
50 Explain Hierarchical Clustering for Text. TDS – Hierarchical Clustering Google, Amazon, Facebook Medium Unsupervised Learning
51 What is DBSCAN in the context of NLP? TDS – DBSCAN Google, Facebook, Amazon Medium Unsupervised Learning
52 Explain the process of Fine-tuning Pre-trained Language Models. TDS – Fine-tuning NLP Google, Amazon, Facebook Hard Transfer Learning
53 What is Transfer Learning in NLP? Analytics Vidhya – Transfer Learning Google, Facebook, Amazon Medium Transfer Learning
54 What is Zero-Shot Classification in NLP? TDS – Zero-Shot Learning Google, Amazon, Facebook Hard Transfer Learning
55 What is Few-Shot Learning in NLP? TDS – Few-Shot Learning Google, Facebook, Amazon Hard Transfer Learning
56 Explain Adversarial Attacks on NLP Models. TDS – Adversarial NLP Google, Facebook, Amazon Hard Security, Robustness
57 Discuss Bias in NLP Models. TDS – NLP Bias Google, Amazon, Facebook Hard Ethics, Fairness
58 What are Ethical Considerations in NLP? Analytics Vidhya – Ethical NLP Google, Facebook, Amazon Hard Ethics
59 What is Language Detection? TDS – Language Detection Google, Amazon, Facebook Easy Applications
60 Explain Transliteration in NLP. TDS – Transliteration Google, Facebook, Amazon Medium Applications
61 What is Language Identification? Analytics Vidhya – NLP Basics Google, Amazon, Facebook Easy Applications
62 Explain Query Expansion in Information Retrieval. TDS – Information Retrieval Google, Facebook, Amazon Medium IR, NLP
63 What is Textual Entailment? TDS – Textual Entailment Google, Amazon, Facebook Hard Semantics
64 What is Natural Language Inference (NLI)? TDS – NLI Google, Facebook, Amazon Hard Semantics
65 What are Dialog Systems in NLP? Analytics Vidhya – Dialog Systems Google, Facebook, Amazon Medium Conversational AI
66 Explain Chatbot Architecture. TDS – Chatbots Google, Amazon, Facebook Medium Conversational AI
67 What is Intent Detection in Chatbots? TDS – Intent Detection Google, Facebook, Amazon Medium Conversational AI
68 What is Slot Filling in Conversational Agents? TDS – Slot Filling Google, Amazon, Facebook Medium Conversational AI
69 Explain Conversation Modeling. TDS – Conversation Modeling Google, Facebook, Amazon Hard Conversational AI
70 How is Sentiment Analysis performed using lexicons? Analytics Vidhya – Sentiment Analysis Google, Facebook, Amazon Easy Applications
71 Explain deep learning techniques for sentiment analysis. TDS – Deep Sentiment Google, Amazon, Facebook Medium Deep Learning, Applications
72 What is Sequence-to-Sequence Learning for Chatbots? TDS – Seq2Seq Chatbots Google, Facebook, Amazon Hard Conversational AI
73 Explain the role of Attention in Machine Translation. TDS – Attention in MT Google, Amazon, Facebook Hard Deep Learning, Translation
74 What is Multi-Head Attention? TDS – Multi-Head Attention Google, Facebook, Amazon Hard Transformers
75 Explain the Encoder-Decoder Architecture. TDS – Encoder-Decoder Google, Amazon, Facebook Hard Deep Learning, Transformers
76 What is Beam Search in NLP? TDS – Beam Search Google, Facebook, Amazon Medium Decoding, Generation
77 Explain Back-Translation for Data Augmentation. TDS – Back-Translation Google, Amazon, Facebook Hard Data Augmentation
78 How does GPT generate text? TDS – GPT Generation Google, Facebook, Amazon Hard Language Models, Generation
79 What is Fine-tuning in Language Models? TDS – Fine-tuning Google, Facebook, Amazon Hard Transfer Learning
80 What is a Context Window in Language Models? TDS – Context Window Google, Amazon, Facebook Medium Language Modeling
81 Explain the Transformer Decoder. TDS – Transformer Decoder Google, Facebook, Amazon Hard Transformers
82 Discuss the importance of Embedding Layers in NLP. TDS – Embedding Layers Google, Facebook, Amazon Medium Deep Learning, Embeddings
83 What is Positional Encoding in Transformers? TDS – Positional Encoding Google, Facebook, Amazon Medium Transformers
84 What is Masked Language Modeling? TDS – Masked LM Google, Facebook, Amazon Hard Transformers, Pre-training
85 Explain Next Sentence Prediction in BERT. TDS – Next Sentence Prediction Google, Facebook, Amazon Hard BERT, Pre-training
86 What are Pre-trained Language Models? Analytics Vidhya – Pre-trained Models Google, Facebook, Amazon Easy Transfer Learning
87 Explain Open-Domain Question Answering in NLP. TDS – Question Answering Google, Facebook, Amazon Hard Applications, QA
88 What is Retrieval-Based NLP? TDS – Retrieval-Based Google, Facebook, Amazon Medium Applications, QA
89 Explain Extractive Question Answering. TDS – Extractive QA Google, Facebook, Amazon Hard Applications, QA
90 What is Abstractive Question Answering? TDS – Abstractive QA Google, Facebook, Amazon Hard Applications, QA
91 What is Machine Reading Comprehension? TDS – MRC Google, Facebook, Amazon Hard Applications, QA
92 What are Attention Heads in Transformers? TDS – Attention Heads Google, Facebook, Amazon Hard Transformers
93 Explain Sequence Transduction. TDS – Sequence Transduction Google, Facebook, Amazon Hard Deep Learning, Generation
94 Discuss the role of GPUs in NLP model training. Analytics Vidhya – NLP Infrastructure Google, Facebook, Amazon Medium Infrastructure
95 What is Subword Tokenization (BPE, SentencePiece)? TDS – Subword Tokenization Google, Facebook, Amazon Medium Preprocessing, Tokenization
96 What is a Language Corpus and why is it important? Analytics Vidhya – Language Corpora Google, Facebook, Amazon Easy NLP Resources
97 What are the challenges in Low-Resource Languages? TDS – Low-Resource NLP Google, Facebook, Amazon Hard Applications, Ethics
98 How do you handle Out-of-Vocabulary words in NLP? TDS – OOV Handling Google, Facebook, Amazon Medium Preprocessing, Embeddings
99 What are Transformer Variants and how do they differ? TDS – Transformer Variants Google, Facebook, Amazon Hard Transformers, Models
100 What are the Future Trends in Natural Language Processing? Analytics Vidhya – Future of NLP Google, Facebook, Amazon Medium Trends, Research

Questions asked in Google interview

  • What is Natural Language Processing?
  • Explain Tokenization.
  • What is TF-IDF and its applications.
  • What are Word Embeddings?
  • What is BERT and how does it work?
  • Explain the Attention Mechanism.
  • What is Machine Translation?
  • Explain Text Summarization.
  • What is Sentiment Analysis?
  • What is Named Entity Recognition (NER)?

Questions asked in Facebook interview

  • Explain Tokenization.
  • What is Stop Word Removal?
  • Explain Stemming and Lemmatization.
  • What is the Bag-of-Words Model?
  • What are Word Embeddings (Word2Vec/GloVe/FastText)?
  • Explain the Transformer architecture.
  • What is GPT and its applications in NLP?
  • Explain the Attention Mechanism.
  • What is Sequence-to-Sequence Modeling?
  • What are Dialog Systems in NLP?

Questions asked in Amazon interview

  • What is Natural Language Processing?
  • Explain TF-IDF and its applications.
  • What is Text Classification?
  • What is Topic Modeling (LDA/LSA)?
  • Explain Sentiment Analysis.
  • What is Named Entity Recognition (NER)?
  • Explain Language Modeling.
  • What is Transfer Learning in NLP?
  • What is Fine-tuning Pre-trained Language Models?
  • What are Pre-trained Language Models?

Questions asked in Microsoft interview

  • What is Natural Language Processing?
  • Explain Language Modeling and Perplexity.
  • What is the Transformer architecture?
  • What is BERT and how does it work?
  • Explain Dependency Parsing.
  • What is Text Summarization?
  • Explain Question Answering systems.
  • What is Subword Tokenization?
  • How do you handle Out-of-Vocabulary words?
  • Discuss challenges in low-resource languages.

Questions asked in other interviews

Uber / Flipkart / Ola:
- Explain the Encoder-Decoder Architecture.
- What is Beam Search in NLP?
- How does GPT generate text?
- What is Fine-tuning in Language Models?

Swiggy / Paytm / OYO:
- What is Noise Removal in Text Processing?
- Explain Named Entity Recognition (NER).
- What are Ethical Considerations in NLP?
- How do you handle bias in NLP models?

WhatsApp / Slack / Airbnb:
- What is Natural Language Inference (NLI)?
- Explain the Attention Mechanism.
- What are Dialog Systems in NLP?
- Discuss the future trends in NLP.