2.5.2 - Metrics Used
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 does accuracy measure in AI models?
💡 Hint: Think of it in terms of correct vs incorrect.
Why is precision important?
💡 Hint: Consider scenarios where false positives are problematic.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What does accuracy refer to in AI evaluations?
💡 Hint: Think about what accuracy really means.
True or False: Precision focuses on how many true positive predictions are made compared to all actual positives.
💡 Hint: Remember what precision considers in predictions.
1 more question available
Challenge Problems
Push your limits with advanced challenges
Design a hypothetical AI model for fraud detection and explain how you would use precision and recall to evaluate its effectiveness.
💡 Hint: Consider real-world implications of each metric.
Evaluate a scenario where a confusion matrix shows high false negatives. Propose potential actions to improve model performance.
💡 Hint: Analyze the consequences of false negatives in your context.
Get performance evaluation
Reference links
Supplementary resources to enhance your learning experience.