Practice Deployment and Monitoring of Machine Learning Models - 20 | 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 deployment?

💡 Hint: Think about how models interact with real-time data.

Question 2

Easy

Name one advantage of using containers for model deployment.

💡 Hint: Consider the benefits of separation.

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 does 'model deployment' refer to in machine learning?

  • Integrating model for predictions
  • Training a model
  • Testing a model

💡 Hint: Think about the process of making a model usable in the field.

Question 2

True or False: Data drift can affect model performance.

  • True
  • False

💡 Hint: Consider how changing conditions can impact predictions.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

You have deployed a model to predict customer churn, but its accuracy has dropped in recent months. Describe how you would identify the cause and address it.

💡 Hint: Reflect on how external factors could change customer behavior.

Question 2

If you are running a batch inference system for an e-commerce website where customer behavior changes frequently, how would you modify the pipeline to enhance performance?

💡 Hint: Think about the timing and frequency of data updates.

Challenge and get performance evaluation