Practice Best Practices and Challenges - 20.6 | 20. Deployment and Monitoring of Machine Learning Models | Data Science Advance
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is the purpose of version control in machine learning?

💡 Hint: Think about why it’s important to go back to a previous state.

Question 2

Easy

Define what is meant by reproducibility in the context of machine learning.

💡 Hint: Consider if someone else could get the same results.

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 is the key benefit of using version control in model deployment?

  • Easier collaboration
  • Ensures data security
  • Tracks changes

💡 Hint: Think about why you would need to go back to an earlier state of your model.

Question 2

True or False: Continuous monitoring can help identify data drift.

  • True
  • False

💡 Hint: Consider what happens when the input data changes.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You are deploying a model that begins to show different performance metrics after a few months. What steps would you take to investigate potential data drift?

💡 Hint: Think about how you can track changes over time.

Question 2

Describe a strategy to ensure model fairness and mitigate bias during the deployment process.

💡 Hint: Consider collaboration with ethicists and diverse stakeholders.

Challenge and get performance evaluation