39 interview questions on Natural Language Processing - Fundamentals for developers (2025)

Easy

8 votes579 runs0 comment

What does NER mean?

Data Scientist

NLP (Natural language processing)

named entity recognition

nlp

Constantinat Mar 16, 2022

Easy

3 votes528 runs

2 comments

Tokenization is the process of separating text into words or groups of words.

Data Scientist

NLP (Natural language processing)

nlp

tokenization

Constantinat Sep 19, 2022

Easy

3 votes517 runs0 comment

What is the LDA used for?

Data Scientist

NLP (Natural language processing)

dimensionality reduction

topic modeling

Constantinat Mar 16, 2022

Hard

3 votes271 runs0 comment

Which principle implies that the meaning of a word is determined by the words that frequently appear in its neighboring context?

Data Scientist

NLP (Natural language processing)

Claudioat Jan 25, 2024

Easy

2 votes504 runs0 comment

Morphological segmentation is the process of separating words into individual morphemes and identifying their classes.

Data Scientist

NLP (Natural language processing)

segmentation

morphemes

Constantinat Mar 16, 2022

Medium

2 votes257 runs0 comment

What is a topic modeling in the context of Natural Language Processing?

Data Scientist

NLP (Natural language processing)

Claudioat Jan 25, 2024

Easy

2 votes157 runs0 comment

Co-reference resolution is the task of determining which words or groups of words refer to the same entity.

Data Scientist

NLP (Natural language processing)

coreference resolution

named entity recognition

Constantinat Mar 16, 2022

Easy

1 vote546 runs0 comment

Lemmatization of the term 'went'

Data Scientist

NLP (Natural language processing)

lemmatization

nlp

Constantinat Mar 16, 2022

Easy

1 vote529 runs0 comment

What is the difference between lemmatization and stemming?

Data Scientist

NLP (Natural language processing)

stemming

lemmatization

Constantinat Mar 16, 2022

Easy

1 vote492 runs0 comment

In what context could a sentimental analysis be the most useful?

Data Scientist

NLP (Natural language processing)

sentiment

nlp

Constantinat Mar 16, 2022

Easy

1 vote490 runs0 comment

In which of the following areas, the application of NLP would not be useful?

Data Scientist

NLP (Natural language processing)

basket analysis

nlp

Constantinat Mar 16, 2022

Easy

1 vote484 runs0 comment

Transfer learning is the use of a model trained on other data.

Data Scientist

NLP (Natural language processing)

models

data

Constantinat Mar 16, 2022

Easy

1 vote164 runs0 comment

NLP polarity is the tendency for a word to be positive or negative.

Data Scientist

NLP (Natural language processing)

sentiment analysis

polarity

Constantinat Mar 16, 2022

Easy

1 vote27 runs0 comment

What is the TF-IDF approach?

Data Scientist

NLP (Natural language processing)

Claudioat Jan 25, 2024

Medium

0 vote497 runs0 comment

How does cosine similarity work?

Data Scientist

NLP (Natural language processing)

similarity

cosine

Constantinat Mar 16, 2022

Medium

0 vote496 runs0 comment

What did the Transformer model bring to NLP compared to its predecessors (Glove, Fastest, Word2Vec)?

Data Scientist

NLP (Natural language processing)

word2vec

transformer

nlp

Constantinat Mar 16, 2022

Easy

0 vote492 runs0 comment

Word Sense Disambiguation (WSD) is an algorithm to choose the word that best matches the context.

Data Scientist

NLP (Natural language processing)

word sense disambiguation

disambiguation

Constantinat Mar 16, 2022

Medium

0 vote491 runs0 comment

What is the POS tag used for?

Data Scientist

NLP (Natural language processing)

part-of-speech

tagging

Constantinat Mar 16, 2022

Easy

0 vote490 runs0 comment

Word2Vect allows creating vectors from words

Data Scientist

NLP (Natural language processing)

word2vec

vectors

Constantinat Mar 16, 2022

Easy

0 vote483 runs

1 comment

Which of the following algorithms is the most recent? BERT, GPT-3, or Transformer?

Data Scientist

NLP (Natural language processing)

BERT

NLP

Constantinat Mar 16, 2022

39 interview questions on Natural Language Processing - Fundamentalsfor developers (2025)

Test your technical skills before an interview of Natural Language Processing - Fundamentals with 39 corrected questions. Beginner, Intermediate or Expert level.

What does NER mean?

Tokenization is the process of separating text into words or groups of words.

What is the LDA used for?

Which principle implies that the meaning of a word is determined by the words that frequently appear in its neighboring context?

Morphological segmentation is the process of separating words into individual morphemes and identifying their classes.

What is a topic modeling in the context of Natural Language Processing?

Co-reference resolution is the task of determining which words or groups of words refer to the same entity.

Lemmatization of the term 'went'

What is the difference between lemmatization and stemming?

In what context could a sentimental analysis be the most useful?

In which of the following areas, the application of NLP would not be useful?

Transfer learning is the use of a model trained on other data.

NLP polarity is the tendency for a word to be positive or negative.

What is the TF-IDF approach?

How does cosine similarity work?

What did the Transformer model bring to NLP compared to its predecessors (Glove, Fastest, Word2Vec)?

Word Sense Disambiguation (WSD) is an algorithm to choose the word that best matches the context.

What is the POS tag used for?

Word2Vect allows creating vectors from words

Which of the following algorithms is the most recent? BERT, GPT-3, or Transformer?