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Fun, engaging games to boost memory, math fluency, typing speed, and English skills—perfect for learners of all ages.
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Knowledge
Practice Questions
Test your understanding with targeted questions related to the topic.
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.
Practice 4 more questions and get performance evaluation
Interactive Quizzes
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
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.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
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.
Question 2
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.
Challenge and get performance evaluation