Practice Transformers - 9.6.3 | 9. Natural Language Processing (NLP) | Data Science Advance
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Transformers

9.6.3 - Transformers

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Practice Questions

Test your understanding with targeted questions

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.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

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.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

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.

Challenge 2 Hard

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.

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