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

Easy

8 votes591 runs0 comment

What does NER mean?

Data Scientist

NLP (Natural language processing)

named entity recognition

nlp

Anonymous authorat Mar 16, 2022

Easy

3 votes540 runs

2 comments

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

Data Scientist

NLP (Natural language processing)

nlp

tokenization

Anonymous authorat Sep 19, 2022

Easy

3 votes529 runs0 comment

What is the LDA used for?

Data Scientist

NLP (Natural language processing)

dimensionality reduction

topic modeling

Anonymous authorat Mar 16, 2022

Hard

3 votes283 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 votes515 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

Anonymous authorat Mar 16, 2022

Medium

2 votes268 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 votes162 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

Anonymous authorat Mar 16, 2022

Easy

1 vote557 runs0 comment

Lemmatization of the term 'went'

Data Scientist

NLP (Natural language processing)

lemmatization

nlp

Anonymous authorat Mar 16, 2022

Easy

1 vote540 runs0 comment

What is the difference between lemmatization and stemming?

Data Scientist

NLP (Natural language processing)

stemming

lemmatization

Anonymous authorat Mar 16, 2022

Easy

1 vote503 runs0 comment

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

Data Scientist

NLP (Natural language processing)

sentiment

nlp

Anonymous authorat Mar 16, 2022

Easy

1 vote501 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

Anonymous authorat Mar 16, 2022

Easy

1 vote494 runs0 comment

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

Data Scientist

NLP (Natural language processing)

models

data

Anonymous authorat Mar 16, 2022

Easy

1 vote170 runs0 comment

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

Data Scientist

NLP (Natural language processing)

sentiment analysis

polarity

Anonymous authorat 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 vote508 runs0 comment

How does cosine similarity work?

Data Scientist

NLP (Natural language processing)

similarity

cosine

Anonymous authorat Mar 16, 2022

Medium

0 vote507 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

Anonymous authorat Mar 16, 2022

Easy

0 vote502 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

Anonymous authorat Mar 16, 2022

Medium

0 vote501 runs0 comment

What is the POS tag used for?

Data Scientist

NLP (Natural language processing)

part-of-speech

tagging

Anonymous authorat Mar 16, 2022

Easy

0 vote501 runs0 comment

Word2Vect allows creating vectors from words

Data Scientist

NLP (Natural language processing)

word2vec

vectors

Anonymous authorat Mar 16, 2022

Easy

0 vote493 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

Anonymous authorat 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?