Practice Best Practices - 20.6.1 | 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 version control?

πŸ’‘ Hint: Think about how you can track changes like in documents.

Question 2

Easy

Name one tool used for reproducible pipelines.

πŸ’‘ Hint: Consider tools specifically designed for machine learning.

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 version control?

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

πŸ’‘ 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

πŸ’‘ Hint: Consider the meaning of reproducibility.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

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

πŸ’‘ Hint: Think about how changes in the data might affect model outcomes.

Question 2

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.

πŸ’‘ Hint: Consider how collaboration can be structured and documented.

Challenge and get performance evaluation