Practice Recurrent Neural Networks (rnn) (9.6.1) - Natural Language Processing (NLP)

Practice: Recurrent Neural Networks (RNN)

Lesson 9.6.1Natural Language Processing (NLP)

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9 questions

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6 sample questions

Question 1.
What does RNN stand for?
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Think about networks that process sequences.
Question 2.
What problem do RNNs face during training?
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This problem affects their learning ability.
3Question 3.
What does RNN stand for?
- Recurrent Neural Network
- Random Neural Network
- Regular Neural Network
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Think about how this network type functions.
4Question 4.
RNNs are primarily used for sequential data processing. (True/False)
- True
- False
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Consider what you learned about RNN applications.
Question 5.
Given a paragraph, design a simple RNN that could memorize and output the last two words of each sentence. Describe how you would implement this in a coding framework.
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Focus on input/output structures for the RNN.
Question 6.
Explain how you would address the vanishing gradient problem if tasked with training an RNN on a long document. What techniques or models would you consider?
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Think about models/architectures that improve RNNs.

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