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Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is a Transformer in the context of NLP?
💡 Hint: Think about how it relates to handling sentences.
Question 2
Easy
Define self-attention.
💡 Hint: Consider how it helps understand sentences better.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the primary mechanism used in Transformers to determine the relationships between words?
💡 Hint: Think about how models manage context.
Question 2
True or False: Transformers require sequential processing like RNNs.
💡 Hint: Consider how Transformers handle input.
Solve and get performance evaluation
Push your limits with challenges.
Question 1
Design a basic Transformer architecture for a sentiment analysis task. Explain what components you would include and their roles.
💡 Hint: Think about how the input needs to be transformed and understood.
Question 2
Evaluate the advantages of using Transformers versus RNNs in terms of processing efficiency.
💡 Hint: Consider the implications of processing time and data handling.
Challenge and get performance evaluation