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Practice Questions
Test your understanding with targeted questions related to the topic.
Question 1
Easy
What does deployment mean in the context of data science?
💡 Hint: Think about the final steps after creating a model.
Question 2
Easy
Why is monitoring important after deployment?
💡 Hint: Consider changes in data trends.
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 a data science project?
- Data Collection
- Making a model available for use
- Data Cleaning
💡 Hint: Think of the last phase before starting practical applications.
Question 2
Monitoring a deployed model ensures it continues to deliver accurate results.
- True
- False
💡 Hint: Consider the importance of changes in data.
Solve 1 more question and get performance evaluation
Challenge Problems
Push your limits with challenges.
Question 1
You are tasked with deploying a machine learning model for predicting loan approvals. Discuss the steps to ensure successful deployment, including ways to monitor the model's effectiveness.
💡 Hint: Consider both technical steps and user engagement.
Question 2
Reflect on a scenario where a model fails post-deployment. What are the potential reasons, and how would you address this failure?
💡 Hint: Think about both data and personnel factors.
Challenge and get performance evaluation