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Q.1
Which is based on tagging and is statistically based as opposed to rule based?
NLTK
spaCy
Q.2
From the sentence “Fintech Online Course”, how many bigrams can be created?
1
2
3
4
5
Q.3
A vader compound score of 1.evaluates to
positive sentiment
neutral sentiment
negative sentiment
none of the above
Q.4
Why we use named entity recognition in NLP?
Classify entities into predefined labels
Creating a set of vocabularies
Breaking sentences into words
None
Q.5
How do we get from NLP text analysis to stock price correlation?
Transform some NLP results into features.
Convert parts of speech to categorical variables
Recognize some named entities
VADER it
Q.6
Which are included in named entity recognition?
Time and dates
Nouns
Currency
All of above
Q.7
What does spaCy tagging do?
Identifies more frequent words
Identifies importance and relevance
Identifies word order relationships
Identifies parts of speech
Q.8
Between NLTK and spaCy, which is faster and better for larger datasets?
NLTK
spaCy
Q.9
Between NLTK and spaCy, which is based on tagging and is statistically based as opposed to rule based?
NLTK
spaCy
Q.10
Which is the main Python package we use for NLP?
Scikit-Learn
NLTK
NLP-LIB
PyNLP
Q.11
Which is the process of turning different morphologies (i.e. versions) of a word into its base form?
Lemmatization
Tokenization
Ngrams
Stopwords
Corpus
Q.12
Which step is the process of breaking down documents into smaller units of analysis?
Lemmatization
Tokenization
Ngrams
Stopwords
Corpus
Q.13
Which are multiple word sequences?
Lemmatization
Tokenization
Ngrams
Stopwords
Corpus
Q.14
Which are common words usually removed in an NLP analysis?
Lemmatization
Tokenization
Ngrams
Stopwords
Corpus
Q.15
Which is a collection of documents?
Lemmatization
Tokenization
Ngrams
Stopwords
Corpus
Q.16
Which is a high term frequency and low document frequency?
A high weight in TF-IDF
A low weight in TF-IDF
A bag of words
A corpus
Q.17
Which company's tone analyzer service did we discuss?
Amazon
Apple
Google
IBM
Q.18
Which is the most useful metric from VADER for sentiment analysis?
Positivity
Compound
Negative
Intensity
Q.19
Which function would you use to implement a bag of words by creating a matrix of token counts?
CountVectorizer()
fit_tranform()
get_feature_names()
download()
Q.20
Which function would you use to retrieve the list of unique words?
CountVectorizer()
fit_tranform()
get_feature_names()
download()
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