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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does the CIFAR-10 dataset consist of?
💡 Hint: Think about the number of classes and images in the dataset.
Question 2
Easy
Why is normalization done on image data?
💡 Hint: What range do we typically scale the pixel values to?
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 purpose of reshaping image data?
- To change the color of the image
- To fit the input layer of a CNN
- To compress the image
💡 Hint: Think about how each layer expects its inputs to look.
Question 2
True or False: One-hot encoding is only necessary for binary classification problems.
- True
- False
💡 Hint: Consider how you might represent multiple classes.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Explain how using a diverse dataset can enhance the performance of a CNN. What might happen if the dataset is too homogeneous?
💡 Hint: Think about model adaptability when exposed to a variety of inputs.
Question 2
Consider an instance where you have a very low-resolution dataset. How might this affect normalization and overall model performance?
💡 Hint: What features does a high-resolution dataset provide that might be lost in low resolution?
Challenge and get performance evaluation