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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
Define what a hyperparameter is.
💡 Hint: Think of parameters we set, not those learned from data.
Question 2
Easy
What is grid search used for?
💡 Hint: Consider a comprehensive search method.
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 the primary goal of hyperparameter tuning?
- To reduce model size
- To enhance model performance
- To increase training time
💡 Hint: Think about what tuning really aims for in a model.
Question 2
Is grid search more efficient than random search?
- True
- False
💡 Hint: Consider efficiency and time factors.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You are training a neural network for image classification. You notice it’s struggling to converge. Explain how you would go about hyperparameter tuning to improve performance.
💡 Hint: Think about how each hyperparameter affects learning.
Question 2
Assume you have used grid search and found an optimal set of hyperparameters. Can you justify the next steps you would take if resources are limited?
💡 Hint: Consider efficiency and validating performance.
Challenge and get performance evaluation