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Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is a hyperparameter?
π‘ Hint: Think about configuration settings of a model.
Question 2
Easy
What role do filters play in CNNs?
π‘ Hint: Consider what happens when we apply convolution to data.
Practice 4 more questions and get performance evaluation
Engage in quick quizzes to reinforce what you've learned and check your comprehension.
Question 1
What is a primary role of hyperparameters in CNNs?
π‘ Hint: Think about how hyperparameters differ from regular model parameters.
Question 2
True or False: A higher dropout rate will always improve model performance.
π‘ Hint: Consider the trade-off in regularization techniques.
Solve 1 more question and get performance evaluation
Push your limits with challenges.
Question 1
Design a CNN architecture for image classification. Choose appropriate hyperparameters for filters, dropout rates, and pooling sizes. Justify your choices.
π‘ Hint: Consider the size of your data and the risk of overfitting in your specifications.
Question 2
Critically evaluate the effects of underfitting and overfitting in your model. What hyperparameters could you adjust to address these issues easily?
π‘ Hint: Think about balancing performance and complexity in your model strategy.
Challenge and get performance evaluation