Data Science with Python Certification Data Science with Python Natural Language Processing

Question 1

Which Python library provides the `word_tokenize()` function for splitting text into individual tokens?

Accepted Answer

NLTK

Answer

spaCy

Answer

TextBlob

Answer

Gensim

Question 2

What is the primary purpose of removing stop words in NLP preprocessing?

Accepted Answer

To reduce vocabulary size and eliminate low-information words

Answer

To correct spelling errors in the text

Answer

To convert words to their base grammatical form

Answer

To split sentences into individual characters

Question 3

What is the difference between stemming and lemmatization in NLP?

Accepted Answer

Stemming crudely chops suffixes while lemmatization returns a valid dictionary base form

Answer

Stemming uses a vocabulary lookup while lemmatization applies fixed suffix rules

Answer

Stemming is more accurate than lemmatization in all cases

Answer

They are functionally identical processes with different library implementations

Question 4

In Python's NLTK library, which class implements Porter stemming?

Accepted Answer

nltk.stem.PorterStemmer

Answer

nltk.stem.WordNetLemmatizer

Answer

nltk.stem.SnowballStemmer

Answer

nltk.tokenize.RegexpTokenizer

Question 5

What does a 'corpus' refer to in the context of NLP?

Accepted Answer

A large structured collection of text used for training or analysis

Answer

A single tokenized sentence

Answer

The vocabulary dictionary of a language model

Answer

A confusion matrix for text classification

Question 6

Which of the following best describes a 'bag of words' (BoW) representation?

Accepted Answer

A document representation as an unordered set of word frequency counts

Answer

A sequence model that preserves word order and context

Answer

A word embedding that maps words to dense vectors

Answer

A parse tree showing grammatical structure

Question 7

What does TF-IDF measure in text analysis?

Accepted Answer

The importance of a word to a document relative to a collection of documents

Answer

The total frequency of all terms across all documents

Answer

The average sentence length across a corpus

Answer

The cosine similarity between two document vectors