Practice Activities (4.5.2) - Advanced Supervised Learning & Evaluation (Weeks 8)
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Activities

Practice - Activities

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is an imbalanced dataset?

💡 Hint: Consider how many examples are in each class.

Question 2 Easy

What does ROC stand for?

💡 Hint: Think about what the curve represents.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is AUC in model evaluation?

Area Under the Classification Curve
Area Under the ROC Curve
Accuracy Under the ROC Curve

💡 Hint: Think about how AUC relates to ROC.

Question 2

True or False: Hyperparameters are learned from data during model training.

True
False

💡 Hint: Recall the definition of hyperparameters.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

You are tasked with building a model for detecting spam emails where false negatives are critical. Would you prioritize recall or precision? Justify your choice based on your understanding of ROC and Precision-Recall curves.

💡 Hint: Think about the consequences of missing actual spam emails.

Challenge 2 Hard

While analyzing your learning curves, you notice that both training and validation scores are high and close to each other. Discuss how you would interpret this situation and what actions you might take as a next step.

💡 Hint: Consider what high scores imply about model readiness.

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