Practice Building a Production Pipeline - 20.3 | 20. Deployment and Monitoring of Machine Learning Models | Data Science Advance
K12 Students

Academics

AI-Powered learning for Grades 8–12, aligned with major Indian and international curricula.

Professionals

Professional Courses

Industry-relevant training in Business, Technology, and Design to help professionals and graduates upskill for real-world careers.

Games

Interactive Games

Fun, engaging games to boost memory, math fluency, typing speed, and English skills—perfect for learners of all ages.

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What does CI stand for in MLOps?

💡 Hint: Think of how code changes are managed.

Question 2

Easy

Name one tool that can be used for Continuous Deployment.

💡 Hint: Recall the tools we discussed.

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 Continuous Integration?

  • A method of model evaluation
  • A practice of testing code changes
  • A deployment technique

💡 Hint: Focus on the definition of CI.

Question 2

True or False: Continuous Deployment means manual deployment of validated changes.

  • True
  • False

💡 Hint: Think about how changes are carried out in modern MLOps.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

A team finds that their model frequently breaks after deployment. Describe how implementing CI/CD could resolve this issue.

💡 Hint: Focus on the benefits of automated testing and deployment.

Question 2

Imagine a scenario where a machine learning model needs to be updated weekly. Discuss how a model registry can facilitate this process.

💡 Hint: Consider how version control aids in frequent updates.

Challenge and get performance evaluation