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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What is deployment in data science?
💡 Hint: Think about the purpose of making data science models practical.
Question 2
Easy
Name one way a model can be deployed.
💡 Hint: Consider common tech interfaces we use regularly.
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 purpose of deployment in data science?
- To train the model
- To make the model available to users
- To analyze data
💡 Hint: Think about how insights are shared with stakeholders.
Question 2
True or False: Monitoring is unnecessary after a model is deployed.
- True
- False
💡 Hint: Consider what might happen if parameters change.
Solve 2 more questions and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
Consider a healthcare model that predicts disease outbreaks. How would data drift over time affect its predictions, and what measures can be implemented for its maintenance post-deployment?
💡 Hint: Think about how historical data may differ from current realities.
Question 2
Describe how you would deploy a customer segmentation model for an e-commerce platform. Outline the xpected user interactions and monitoring strategies post-deployment.
💡 Hint: Consider what users might want to achieve with the tool.
Challenge and get performance evaluation