Practice Lab: Building And Training A Basic Cnn For Image Classification Using Keras (6.5)
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Lab: Building and Training a Basic CNN for Image Classification using Keras

Practice - Lab: Building and Training a Basic CNN for Image Classification using Keras

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the recommended range for normalizing image pixel values?

💡 Hint: Consider the typical range of pixel values in images.

Question 2 Easy

Which Keras layer is primarily used to reduce dimensionality in a CNN?

💡 Hint: Think about layers that simplify feature maps.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the primary purpose of normalization in image preprocessing?

To reduce dimensionality
To adjust the scale of pixel values
To improve model interpretability

💡 Hint: Remember the range we aim for with pixel values.

Question 2

True or False: Pooling layers increase parameters in a CNN.

True
False

💡 Hint: Consider what pooling does to the data size.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

How might the architecture of a CNN change if it were designed to classify high-resolution images compared to standard CIFAR-10 images?

💡 Hint: Consider how detail changes with higher resolution.

Challenge 2 Hard

Discuss the impact of adding dropout layers in a CNN. Where would you place them, and what benefits would they offer?

💡 Hint: Think about the balance between learning and overfitting.

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Reference links

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