Practice Model Monitoring and Continuous Learning - 14.5 | 14. Machine Learning Pipelines and Automation | Data Science Advance
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Model Monitoring and Continuous Learning

14.5 - Model Monitoring and Continuous Learning

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Learning

Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is model monitoring?

💡 Hint: Think about why we check model performance.

Question 2 Easy

Name a tool for monitoring model performance.

💡 Hint: Consider tools commonly used in data science.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

Question 1

What key issue does model monitoring address?

Data drift
Overfitting
Bias in data

💡 Hint: Focus on the changes that happen after model deployment.

Question 2

True or False: Automation tools can only alert when there are errors in models.

True
False

💡 Hint: Consider what continuous monitoring can accomplish.

2 more questions available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

Imagine your customer's purchasing patterns change drastically over time. How would you ensure your recommendation model remains effective?

💡 Hint: Consider the relationship between user behavior data and recommendations.

Challenge 2 Hard

You discover that your model's accuracy has dropped from 90% to 75%. How would you investigate and address this issue?

💡 Hint: Think about the data and environment changes that could affect model accuracy.

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