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

Test your understanding with targeted questions related to the topic.

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.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

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.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

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.

Question 2

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

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

Challenge and get performance evaluation