Practice Tools for Monitoring - 20.4.3 | 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 data drift?

💡 Hint: Think about changes in patterns of incoming data.

Question 2

Easy

Name one tool for monitoring machine learning models.

💡 Hint: One tool is an open-source monitoring system.

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 machine learning models?

  • To improve model accuracy
  • To ensure models adapt to data changes
  • To visualize data

💡 Hint: Consider the reasons for deploying a model continuously.

Question 2

True or False: Concept drift refers to changes in data distribution.

  • True
  • False

💡 Hint: Remember the definitions of drift types.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design a monitoring strategy for a new image recognition model deployed in a live environment. What tools would you use and why?

💡 Hint: Think about how each tool contributes to monitoring.

Question 2

Evaluate the implications of a model not being monitored over a six-month period in a rapidly changing data environment.

💡 Hint: Consider what happens to models as data changes.

Challenge and get performance evaluation