Text Mining with Python (week 9)
Quiz
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Other
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University
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Practice Problem
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Hard
Mikhail Bukhtoyarov
Used 1+ times
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Enhance your content in a minute
7 questions
Show all answers
1.
MULTIPLE SELECT QUESTION
30 sec • 1 pt
Natural language processing (NLP) is a subfield of ... and ... that uses machine learning to enable computers to understand and communicate with human language.
2.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
What is the correct order of preprocessing the text for further mining?
tokenization, lemmatization, and removing stop words
lemmatization, tokenization, and removing stop words
lemmatization, removing stop words, and tokenization
removing stop words, lemmatization, and tokenization
3.
MULTIPLE CHOICE QUESTION
1 min • 1 pt
What does this piece of code do?
def most_common(df, top_n=10):
all_words = [word for word in ' '.join(df['processed_comments']).split() if word not in string.punctuation]
word_counts = Counter(all_words)
top_10_words = word_counts.most_common(top_n)
return top_10_words
identifies the most recurrent themes or issues
tokenizes the textual data
categorizes comments
scrapes the html files to csv
4.
MULTIPLE SELECT QUESTION
1 min • 1 pt
What Python libraries are used for text mining?
NLTK
Pandas
BeutifulSoup
TextBlob
5.
MULTIPLE SELECT QUESTION
1 min • 1 pt
What can NLTK (natural language toolkit) be used for?
stemming and lemmatization
tokenization
sentiment analysis
speech recognition
6.
MULTIPLE CHOICE QUESTION
30 sec • 1 pt
What is Pandas library used for?
working with MS Office files
building neural networks
data manipulation and analysis
speech recognition
7.
MULTIPLE CHOICE QUESTION
45 sec • 1 pt
The goal of sentiment analysis is to determine the overall sentiment polarity of a piece of text, which can be ...
positive, negative, or neutral
positive, negative, emotional, or neutral
sentimental, rational
poetical, prosaic, academic, legal, etc.
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