Practice Modelling (15.2.3) - Natural Language Processing (NLP)

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9 questions

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6 sample questions

Question 1.
What is the primary goal of modelling in NLP?
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Think about why we need data and algorithms.
Question 2.
Name one task that uses modelling.
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Consider NLP applications that categorize or analyze text.
3Question 3.
What does 'modelling' in NLP refer to?
- Data cleaning
- Using algorithms to train models
- Feature extraction
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Think of what comes after data is prepared.
4Question 4.
True or false: Sentiment analysis is one of the tasks performed during the modelling phase in NLP.
- True
- False
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Recall the tasks discussed previously.
Question 5.
Consider a scenario where you have a dataset of tweets labeled as 'positive', 'negative', or 'neutral'. Describe the steps you would take to build a sentiment analysis model.
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Think about the standard NLP steps we've covered.
Question 6.
You are tasked to design a text classification application for product reviews. What features would you consider extracting and why?
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Reflect on the different feature extraction techniques we've discussed.

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