Practice Monitoring and Maintenance - 1.4.8 | Introduction to Data Science | Data Science Basic
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1.4.8 - Monitoring and Maintenance

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is monitoring in the context of data science?

💡 Hint: Think about how we track a model's performance after it's deployed.

Question 2

Easy

What does maintenance involve for a data science model?

💡 Hint: Consider what actions you would take if your model's performance changes.

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 primary purpose of monitoring a data science model?

  • To enhance data collection
  • To check model performance
  • To reduce data input

💡 Hint: Think about what happens after a model is deployed.

Question 2

True or False: Maintenance of a model involves only updating its software.

  • True
  • False

💡 Hint: What else might we do to keep a model reliable?

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Your organization has a model predicting customer churn. After six months, you notice inaccuracies in forecasts. Discuss the steps you would take to diagnose and correct the issue.

💡 Hint: What do you need to know to restore accuracy?

Question 2

Design a monitoring framework for a fraud detection model that identifies transactions. What key indicators would you track, and how would you respond to performance drift?

💡 Hint: Consider what would alert you to fraudulent activities in a system.

Challenge and get performance evaluation