7.5 - Evaluation
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 is accuracy in model evaluation?
💡 Hint: Think about how many correct predictions were made out of all predictions.
Define precision.
💡 Hint: Remember this focuses on only the positives predicted.
4 more questions available
Interactive Quizzes
Quick quizzes to reinforce your learning
What does precision measure in model evaluation?
💡 Hint: Recall that precision is concerned with positive predictions only.
True or False: The F1 Score is the average of accuracy and recall.
💡 Hint: Think about how F1 combines precision and recall instead of including accuracy.
2 more questions available
Challenge Problems
Push your limits with advanced challenges
You have a confusion matrix with TP=50, TN=30, FP=10, FN=10. Calculate accuracy, precision, and recall.
💡 Hint: Use the definitions of each metric to guide your calculations.
Discuss the potential biases in AI evaluating models based exclusively on accuracy.
💡 Hint: Consider how performance metrics like precision and recall could help reveal more about a model's true effectiveness.
Get performance evaluation
Reference links
Supplementary resources to enhance your learning experience.