Practice Federated Learning - 6.2 | AI Ethics, Bias, and Responsible AI | Artificial Intelligence Advance
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is federated learning?

💡 Hint: Think about where data is stored.

Question 2

Easy

Why is data privacy important in federated learning?

💡 Hint: Consider the risks of data breaches.

Practice 4 more questions and get performance evaluation

Interactive Quizzes

Engage in quick quizzes to reinforce what you've learned and check your comprehension.

Question 1

What does federated learning primarily aim to protect?

  • Data privacy
  • Model accuracy
  • Computation speed

💡 Hint: Think about what stays on the device.

Question 2

True or False: In federated learning, data needs to be centralized for model training.

  • True
  • False

💡 Hint: Recall how federated learning operates.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Suppose a healthcare provider uses federated learning but faces data imbalance across its hospitals. Propose a solution to this issue.

💡 Hint: Consider methods that can help offset data discrepancies.

Question 2

A mobile app implements federated learning for predictive typing but detects skewed predictions. What steps would you suggest to address this skew?

💡 Hint: Think about diversity in the datasets contributing to the model.

Challenge and get performance evaluation