Practice Lab Objectives (6.5.1) - Introduction to Deep Learning (Weeks 12)
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Lab Objectives

Practice - Lab Objectives

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is the benefit of normalizing data?

💡 Hint: Consider how data is represented to the model.

Question 2 Easy

Name a common optimizer used when compiling CNNs.

💡 Hint: Think about widely adopted techniques.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What are the key components to specify when compiling a model?

Loss Function
Metrics
Number of Epochs
Optimizer
Loss Function
Metrics
Learning Rate
Layers
Activation Function

💡 Hint: Consider what controls the model's learning.

Question 2

True or False: The pooling layer increases the spatial dimensions of the output feature maps.

True
False

💡 Hint: Think about how pooling affects the size of feature maps.

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Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Given a dataset where images are of varying sizes, how would you adjust your preprocessing steps?

💡 Hint: Think about how CNNs expect input dimensions.

Challenge 2 Hard

Design a simple CNN architecture for a classification task involving ten categories.

💡 Hint: Recall the structure discussed in class.

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