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FinTech 12-3 NLP

Total questions: 8

Worksheet time: 4mins

Name
Class
Date
1.

Which were objectives for NLP day 3?

a)

Using spaCy

b)

Correlate text features to series like stock prices

c)

Use parts of speech tagged text

d)

Create a chatbot

2.

Between NLTK and spaCy, which is based on tagging and is statistically based as opposed to rule based?

a)

NLTK

b)

spaCy

3.

Between NLTK and spaCy, which is faster and better for larger datasets?

a)

NLTK

b)

spaCy

4.

What does spaCy tagging do?

a)

Identifies more frequent words

b)

Identifies importance and relevance

c)

Identifies word order relationships

d)

Identifies parts of speech

5.

Which are included in named entity recognition?

a)

Sentiment

b)

Nouns

c)

Currency

d)

Time and dates

6.

How do we get from NLP text analysis to stock price correlation?

a)

Transform some NLP results into features.

b)

Convert parts of speech to categorical variables

c)

Recognize some named entities

d)

VADER it

7.

How was NLP day 3 for you?

4 lines
8.

Any suggestions for improvement?

4 lines