WorksheetsFinTech 12-2 NLP
Total questions: 10
Worksheet time: 5mins
What were the objectives of NLP day 2?
Analyze sentiments and tone from news feeds.
Use NLTK and VADER to classify news as positive, negative, or neutral.
Predict stock movements based on sentiment analysis.
Perform data preparation techniques for sentiment analysis.
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
Which is a model of measuring the incidence of known words?
A high weight in TF-IDF
A low weight in TF-IDF
A bag of words
A corpus
Which function would you use to retrieve the list of unique words?
CountVectorizer()
fit_tranform()
get_feature_names()
download()
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()
Which news sources did we use?
News API
NY Times
Bloomberg
Reuters
Which is the most useful metric from VADER for sentiment analysis?
Positivity
Compound
Negative
Intensity
Which company's tone analyzer service did we discuss?
Amazon
Apple
IBM
How was NLP day 2 for you?
Any suggestions for improvement?
