Practice Compiling The Cnn (6.5.2.3) - Introduction to Deep Learning (Weeks 12)
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Compiling the CNN

Practice - Compiling the CNN

Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is a filter in a CNN?

💡 Hint: Think of it as a template for looking at data.

Question 2 Easy

What does pooling do in a CNN?

💡 Hint: It helps in summarizing the information.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the primary purpose of convolutional layers in a CNN?

To reduce dimensionality
To perform feature extraction
To normalize outputs

💡 Hint: Think about what CNNs do for image understanding.

Question 2

True or False: Batch normalization is used to increase the learning rate during CNN training.

True
False

💡 Hint: Consider stability vs. acceleration.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design a CNN architecture for distinguishing different species of flowers from images, incorporating dropout and batch normalization.

💡 Hint: Consider the diversity of features present in flower images.

Challenge 2 Hard

Analyze the impact of modifying the filter size from 3x3 to 5x5 in a convolutional layer. What are the potential advantages or disadvantages?

💡 Hint: Think about how bigger tools can gather more but might overlook finer details.

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Reference links

Supplementary resources to enhance your learning experience.