Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define accuracy in the context of classification tasks.
💡 Hint: Think about the correct predictions versus the total predictions.
Question 2
Easy
What does precision measure?
💡 Hint: Consider what true positives are.
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Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the main purpose of evaluation metrics in NLP?
💡 Hint: Think about how we determine whether a model is good or not.
Question 2
Which metric is NOT commonly used for evaluating classification tasks?
- Accuracy
- Perplexity
- F1 Score
💡 Hint: Remember the specific application of each metric.
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Challenge Problems
Push your limits with challenges.
Question 1
A model for identifying spam in emails achieved a high accuracy but failed to catch many actual spam emails. Discuss how precision and recall provide a clearer picture of the model's effectiveness.
💡 Hint: Consider how the model's predictions relate to the actual spam emails.
Question 2
Propose how you would evaluate a summarization model's output. What metrics would you choose, and why?
💡 Hint: Think about what you want to measure in the output quality.
Challenge and get performance evaluation