Amazon
MLS-C01 · Question #208
A data scientist is reviewing customer comments about a company's products. The data scientist needs to present an initial exploratory analysis by using charts and a word cloud. The data scientist…
The correct answer is C. Stemming D. Term frequency-inverse document frequency (TF-IDF). Sentiment analysis is the result of analysis, not feature engineering.
Exploratory Data Analysis
Question
A data scientist is reviewing customer comments about a company's products. The data scientist needs to present an initial exploratory analysis by using charts and a word cloud. The data scientist must use feature engineering techniques to prepare this analysis before starting a natural language processing (NLP) model. Which combination of feature engineering techniques should the data scientist use to meet these requirements? (Choose two.)
Options
- ANamed entity recognition
- BCoreference
- CStemming
- DTerm frequency-inverse document frequency (TF-IDF)
- ESentiment analysis
How the community answered
(26 responses)- A15% (4)
- B4% (1)
- C73% (19)
- E8% (2)
Explanation
Sentiment analysis is the result of analysis, not feature engineering.
Topics
#Text Preprocessing#Feature Engineering#NLP Fundamentals#EDA Techniques
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