Practice Bag of Words (BoW) - 9.4.1 | 9. Natural Language Processing (NLP) | Data Science Advance
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Bag of Words (BoW)

9.4.1 - Bag of Words (BoW)

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What does Bag of Words represent in text analysis?

💡 Hint: Think about word counting.

Question 2 Easy

What is the purpose of stop word removal?

💡 Hint: Consider which words are unnecessary.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does the BoW model focus on?

Word meaning
Word frequency
Word order

💡 Hint: Consider what aspect of text BoW emphasizes.

Question 2

Is tokenization an important part of creating a BoW model?

True
False

💡 Hint: Think about how we extract words from text.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Create a Bag of Words vector for the following sentences: 'Cats are fun. Dogs are great. Cats are better than dogs.'

💡 Hint: Count how many times each unique word appears.

Challenge 2 Hard

Discuss the disadvantages of using the Bag of Words model for text analysis.

💡 Hint: Consider what details BoW overlooks when analyzing text.

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