Practice Challenges (13.3.3) - Privacy-Aware and Robust Machine Learning
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Challenges

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Practice Questions

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Question 1 Easy

What does communication overhead refer to in federated learning?

💡 Hint: Think about the resources required to keep the communication flowing.

Question 2 Easy

What does data heterogeneity mean?

💡 Hint: Consider how data might vary across different users or devices.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is one main challenge of federated learning?

Data privacy
Communication overhead
Model complexity

💡 Hint: Remember the different challenges we discussed in class.

Question 2

True or False: Data heterogeneity refers to clients having identical data distributions.

True
False

💡 Hint: Think about the variability in data coming from different users.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design a federated learning system that minimizes communication overhead. What strategies would you implement?

💡 Hint: Consider how the volume of data can be reduced.

Challenge 2 Hard

Propose a methodology for detecting malicious clients in your federated learning framework. What steps would you take?

💡 Hint: Think about securing data integrity from the client side.

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