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3 cards from this section. Quick, good the night before a test.
What does the CIFAR-10 dataset consist of?
Think about the number of classes in CIFAR-10.
How many images are contained in the MNIST dataset?
Consider how many digits are represented and the dataset size.
What is the primary purpose of the ImageNet dataset?
Think about what tasks ImageNet is most commonly used for.
True or False: CIFAR-10 contains images of various environments like forests and mountains.
Recall the specific classes included in CIFAR-10.
Design an experiment to compare the performance of models trained on CIFAR-10 versus those trained on ImageNet. What metrics would you use?
Consider what makes evaluations fair and relevant.
Discuss the implications of using synthetic data to augment datasets such as MNIST or CIFAR-10. How can this impact model training?
Think about the balance between data quality and augmentation.
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