Practice Transformers - 9.6.3 | 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 is a transformer?

💡 Hint: Think about how it processes language differently than previous models.

Question 2

Easy

Define self-attention.

💡 Hint: Consider what it means to focus on 'parts' in a sentence.

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 a transformer use instead of recurrence?

  • Convolution
  • Self-Attention
  • Pooling

💡 Hint: Think about the ways transformers analyze data differently.

Question 2

True or False: Positional encoding is not important for transformers.

  • True
  • False

💡 Hint: Consider why the order of words can change the meaning.

Solve and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

How would the introduction of multi-head attention change the previously linear method of processing language? Illustrate this with an example.

💡 Hint: Consider the difference between reading each line of a book separately versus discussing its themes and characters all at once.

Question 2

In what situations might positional encoding fail? Provide scenarios and suggest possible modifications.

💡 Hint: Think about sentences that can have varied meanings based on different contexts.

Challenge and get performance evaluation