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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is overfitting?
💡 Hint: Think about the training accuracy versus test accuracy.
Question 2
Easy
Name one technique to prevent overfitting.
💡 Hint: It adds a penalty to complexity.
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 a sign of overfitting?
- High validation accuracy
- Low training accuracy
- High training accuracy and low validation accuracy
💡 Hint: Think about the difference between training and validation datasets.
Question 2
Is early stopping a method to prevent overfitting?
- True
- False
💡 Hint: Consider training dynamics.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Consider a dataset with numerous features. Describe a systematic approach to ensure your model does not overfit while tuning for the best performance.
💡 Hint: Think about balancing feature sets and evaluating performance.
Question 2
After implementing a model with an accuracy drop on test data, what steps would you take to analyze and rectify the issue?
💡 Hint: Consider the possible reasons for discrepancies in performance.
Challenge and get performance evaluation