Practice Best Practices - 20.6.1 | 20. Deployment and Monitoring of Machine Learning Models | Data Science Advance
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Best Practices

20.6.1 - Best Practices

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is version control?

💡 Hint: Think about how you can track changes like in documents.

Question 2 Easy

Name one tool used for reproducible pipelines.

💡 Hint: Consider tools specifically designed for machine learning.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What is the primary purpose of version control?

To manage project budgets
To track changes in models
To analyze data trends

💡 Hint: Think about how changes need to be documented in data science.

Question 2

True or False: Reproducible pipelines ensure that every experiment is unique.

True
False

💡 Hint: Consider the meaning of reproducibility.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Consider a scenario where a deployed model starts showing poor performance. Outline your steps for troubleshooting and monitoring.

💡 Hint: Think about how changes in the data might affect model outcomes.

Challenge 2 Hard

You have a team of data scientists who are experiencing difficulties collaborating on model development without version control. Propose a solution and describe its implementation.

💡 Hint: Consider how collaboration can be structured and documented.

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