Practice Model Lifecycle Management - 20.5.1 | 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 model retraining?

πŸ’‘ Hint: Think about why models might need updates.

Question 2

Easy

What is data drift?

πŸ’‘ Hint: Consider how data can evolve over time.

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 a reason for retraining a model?

  • Data drift
  • Model overtraining
  • Static data

πŸ’‘ Hint: Recall the factors that can affect model relevance.

Question 2

True or False: Automated pipelines eliminate the need for human intervention entirely.

  • True
  • False

πŸ’‘ Hint: Consider the role of humans in monitoring models.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design an automated retraining pipeline for a customer segmentation model, addressing potential challenges.

πŸ’‘ Hint: Consider the different components involved in deploying and managing machine learning models.

Question 2

Evaluate the impact of concept drift versus data drift on a fraud detection model.

πŸ’‘ Hint: Focus on how changes in patterns can challenge a model's ability to function accurately.

Challenge and get performance evaluation