12 - Evaluation Methodologies of AI Models
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Practice Questions
Test your understanding with targeted questions
What does a confusion matrix show?
💡 Hint: Think about how we compare correct versus incorrect predictions.
Define accuracy in the context of model evaluation.
💡 Hint: Consider the total number of correct predictions.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What does a confusion matrix compare?
💡 Hint: It's primarily focused on predictions.
True or False: Accuracy is always a reliable measure of model performance.
💡 Hint: Consider scenarios where accuracy may not reflect true performance.
3 more questions available
Challenge Problems
Push your limits with advanced challenges
Suppose you have an imbalanced dataset with 90% negatives and 10% positives. You want to evaluate the model's performance strictly for the positive class. Which metric would you rely on and why?
💡 Hint: Think about the importance of false positives in your evaluation.
Design a small experiment where you apply both train-test split and k-fold cross-validation on the same dataset. Discuss the findings regarding model performance using these two methods.
💡 Hint: Consider how data partitions impact learning.
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