12.6 - Hyperparameter Tuning with Evaluation
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Practice Questions
Test your understanding with targeted questions
What is a hyperparameter?
💡 Hint: Think about parameters that aren't learned from the data.
Name two methods used for hyperparameter tuning.
💡 Hint: Consider methods that involve testing combinations of settings.
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Interactive Quizzes
Quick quizzes to reinforce your learning
What is Grid Search?
💡 Hint: Consider which method exhaustively checks all combinations.
True or False: Random Search tests all possible combinations of hyperparameters.
💡 Hint: Think about the nature of random sampling versus a full evaluation.
1 more question available
Challenge Problems
Push your limits with advanced challenges
Provide a detailed explanation of how you would approach hyperparameter tuning for a support vector machine model, considering the need to avoid overfitting.
💡 Hint: Reflect on your understanding of the techniques in balancing thoroughness with efficiency.
Suppose you are tuning a complex neural network. Discuss how you would utilize learning curves alongside the tuning process.
💡 Hint: Think about how visualizing performance aids in making decisions.
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