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Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does evaluation in AI aim to assess?
💡 Hint: Think about model predictions on new data.
Question 2
Easy
Define accuracy in the context of AI evaluation.
💡 Hint: Consider how correct predictions relate to total predictions.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is the primary goal of evaluation in AI?
💡 Hint: Remember the context of model performance.
Question 2
True or False: Overfitting occurs when a model performs well on unseen data.
💡 Hint: Think about how it contrasts with generalization.
Solve 3 more questions and get performance evaluation
Push your limits with challenges.
Question 1
A model predicts whether an email is spam or not. After receiving 1,000 emails, it correctly identifies 760 non-spam emails and mistakenly labels 25 legitimate emails as spam (false positives). Calculate the model's precision.
💡 Hint: Focus on the formula for precision and the definitions of true positives and false positives.
Question 2
You are tasked with creating a robust model for detecting fraudulent transactions. How would you design an evaluation strategy ensuring you account for both precision and recall given that fraudulent cases are rare?
💡 Hint: Discuss methods to handle imbalanced datasets along with the evaluation metrics.
Challenge and get performance evaluation