Practice Contextual Embeddings (2.2) - Natural Language Processing (NLP) in Depth

Practice: Contextual Embeddings

Lesson 2.2Natural Language Processing (NLP) in Depth

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9 questions

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6 sample questions

Question 1.
What is the main advantage of contextual embeddings over static embeddings?
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Think about meaning changes in different sentences.
Question 2.
Give an example of a word with different meanings in different contexts.
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Consider how the surrounding words change the meaning.
3Question 3.
What do contextual embeddings help in determining?
- Static meanings of words
- Variable meanings of words based on context
- Only grammatical structures
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Think about how each sentence can change a word's meaning.
4Question 4.
BERT is a model that processes text bi-directionally.
- True
- False
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Consider the way it reads word order.
Question 5.
Provide a multifaceted sentence using the word 'bark' and explain how contextual embeddings would differentiate its meanings.
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Identify which phrase provides the key context.
Question 6.
Explain how GPT could be improved using feedback from its contextual outputs in conversational applications.
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Consider the feedback loops in conversational AI.

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