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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define correctness in the context of AI.
💡 Hint: Think about accurate predictions.
Question 2
Easy
What does it mean for a model to be robust?
💡 Hint: Consider how it reacts to different inputs.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is meant by the term correctness in AI evaluation?
- Accuracy of predictions
- Speed of processing
- Complexity of the model
💡 Hint: Focus on the result of the predictions.
Question 2
Is robustness important for AI models?
- True
- False
💡 Hint: Think about different scenarios.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Analytically evaluate a situation where lacking robustness led to a significant failure in an AI application.
💡 Hint: Reflect on how diverse data scenarios are essential.
Question 2
Critically examine how biases formed from inadequate evaluation can perpetuate through AI applications.
💡 Hint: Identify the importance of evaluation to mitigate such impact.
Challenge and get performance evaluation