NLP Interview Questions and Answers
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Freshers / Beginner level questions & answers
Ques 1. What is Natural Language Processing (NLP)?
NLP is a field of artificial intelligence that focuses on the interaction between computers and humans using natural language.
Example:
An example of NLP is sentiment analysis, where a computer analyzes text to determine the sentiment expressed (positive, negative, or neutral).
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Ques 2. What is Named Entity Recognition (NER)?
NER is a process in NLP that involves identifying and classifying entities (such as names of people, locations, organizations) in text.
Example:
In the sentence 'Apple Inc. is located in Cupertino,' NER would identify 'Apple Inc.' as an organization and 'Cupertino' as a location.
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Ques 3. Explain the concept of a Bag-of-Words (BoW) model.
A BoW model represents a document as an unordered set of words, disregarding grammar and word order but keeping track of word frequency.
Example:
In a BoW representation, the sentence 'I love programming, and I love to read' might be represented as {'I': 2, 'love': 2, 'programming': 1, 'to': 1, 'read': 1}.
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Ques 4. What are stop words, and why are they often removed in NLP preprocessing?
Stop words are common words (e.g., 'the', 'and', 'is') that are often removed during preprocessing to reduce dimensionality and focus on more meaningful words.
Example:
In sentiment analysis, stop words may not contribute much to sentiment and can be excluded to improve model efficiency.
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