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

20.3 - Building a Production Pipeline

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Practice Questions

Test your understanding with targeted questions

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.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

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.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

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.

Challenge 2 Hard

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.

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