Practice Feature Extraction Techniques (9.4) - Natural Language Processing (NLP)

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6 sample questions

Question 1.
What is the primary focus of the Bag of Words model?
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Think about how the model treats words in a document.
Question 2.
Name one advantage of TF-IDF over Bag of Words.
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Consider how it weights terms.
3Question 3.
Which technique focuses on word frequency count and ignores word order?
- Bag of Words
- TF-IDF
- Word Embeddings
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Think of a simple counting approach.
4Question 4.
True or False: TF-IDF gives higher weights to common words across a document.
- True
- False
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Consider the meaning of 'inverse' in IDF.
Question 5.
Design a simple document similarity algorithm using Bag of Words and explain how you would implement it.
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Think about vector mathematics for similarity.
Question 6.
Functionally assess the application of FastText in an NLP system that handles diverse languages - what are the pros and cons?
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Consider context and different language structures.

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