Practice Best Practices - 20.6.1 | 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 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.

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

💡 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.

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.

💡 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.

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

Challenge and get performance evaluation