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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is the purpose of a training set in AI?
💡 Hint: Think about the initial learning phase of the model.
Question 2
Easy
Why do we need a separate validation set?
💡 Hint: Consider the aspect of ensuring the model generalizes.
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 does the training set allow the model to do?
- Learn patterns
- Evaluate performance
- Tune parameters
💡 Hint: Focus on the purpose of each dataset.
Question 2
True or False: The test set can be used during model training.
- True
- False
💡 Hint: Think about the implications of evaluation integrity.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Design a hypothetical scenario where a model fails due to improper use of training, validation, and test datasets. Clearly explain how the failure occurred and suggest a proper dataset strategy.
💡 Hint: Think about how unseen data can impact performance.
Question 2
Critique a case where an organization decided to merge their validation set and training set, leading to lower accuracy in the model’s practical application. What alternatives could they have pursued?
💡 Hint: What outcomes derive from validation merging?
Challenge and get performance evaluation