9.6 - Deep Learning in NLP
Enroll to start learning
You’ve not yet enrolled in this course. Please enroll for free to listen to audio lessons, classroom podcasts and take practice test.
Practice Questions
Test your understanding with targeted questions
What is the main advantage of RNNs over traditional neural networks?
💡 Hint: Think about how data is structured over time.
What issue do LSTMs aim to solve in RNNs?
💡 Hint: Consider the flow of information through layers in a sequence.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What is an advantage of Transformers over RNNs?
💡 Hint: Think about how information is processed simultaneously.
True or False: LSTMs are specifically designed to address vanishing gradient problems in neural networks.
💡 Hint: Consider the stability of gradients during training.
1 more question available
Challenge Problems
Push your limits with advanced challenges
Given a dataset of text for sentiment analysis, outline how you would choose between using RNNs, LSTMs, or Transformers as your model. Discuss the impact on performance.
💡 Hint: Consider the data complexity and processing needs.
Explain how you might combine Transformers with traditional NLP techniques for a hybrid model. Provide a scenario where this could be effective.
💡 Hint: Think about how models collaborate to optimize performance.
Get performance evaluation
Reference links
Supplementary resources to enhance your learning experience.