Q.1.
Which is based on tagging and is statistically based as opposed to rule based?
Q.2.
From the sentence “Fintech Online Course”, how many bigrams can be created?
Q.3.
A vader compound score of 1.evaluates to
Q.4.
Why we use named entity recognition in NLP?
Q.5.
How do we get from NLP text analysis to stock price correlation?
Q.6.
Which are included in named entity recognition?
Q.7.
What does spaCy tagging do?
Q.8.
Between NLTK and spaCy, which is faster and better for larger datasets?
Q.9.
Between NLTK and spaCy, which is based on tagging and is statistically based as opposed to rule based?
Q.10.
Which is the main Python package we use for NLP?
Q.11.
Which is the process of turning different morphologies (i.e. versions) of a word into its base form?
Q.12.
Which step is the process of breaking down documents into smaller units of analysis?
Q.13.
Which are multiple word sequences?
Q.14.
Which are common words usually removed in an NLP analysis?
Q.15.
Which is a collection of documents?
Q.16.
Which is a high term frequency and low document frequency?
Q.17.
Which company's tone analyzer service did we discuss?
Q.18.
Which is the most useful metric from VADER for sentiment analysis?
Q.19.
Which function would you use to implement a bag of words by creating a matrix of token counts?
Q.20.
Which function would you use to retrieve the list of unique words?