Practice Federated Learning (fl) (13.3) - Privacy-Aware and Robust Machine Learning
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Federated Learning (FL)

Practice - Federated Learning (FL)

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is one advantage of Federated Learning?

💡 Hint: Think about where the data resides during training.

Question 2 Easy

What does the central server do in Federated Learning?

💡 Hint: Consider what information gets shared.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What does Federated Learning primarily help enhance?

Data exposure
Data privacy
Data centralization

💡 Hint: Think about the primary goal of keeping user data secure.

Question 2

True or False: Federated Learning sends raw data to the central server.

True
False

💡 Hint: Consider what is shared with the central server.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Design a Federated Learning system for a healthcare application that needs to comply with HIPAA regulations. Discuss how you would ensure data security and model integrity.

💡 Hint: Think about both patient privacy and system security in your design.

Challenge 2 Hard

Evaluate the implications of non-IID data when training across multiple client devices in Federated Learning. How would you address this issue in practical scenarios?

💡 Hint: Consider the different distributions of data that could exist among clients.

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