Practice Deployment Scenarios - 20.1.2 | 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 batch inference?

💡 Hint: Think about periodic processing of data.

Question 2

Easy

Name a scenario where online inference is utilized.

💡 Hint: Consider instant feedback applications.

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 batch inference involve?

  • Real-time predictions
  • Predictions on large datasets at intervals
  • Only predictions on small datasets

💡 Hint: Think about how often predictions are made.

Question 2

Online inference is best for scenarios where?

  • True
  • False

💡 Hint: Consider applications that benefit from instant feedback.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Create a strategy for an online retail platform planning to transition from batch inference to online inference. Discuss potential challenges and solutions.

💡 Hint: Focus on balancing efficiency and user experience.

Question 2

How would the deployment of an ML model for a self-driving car involve aspects of both edge and online inference? Discuss operational advantages.

💡 Hint: Consider the implications of decision-making speed for safety and efficiency.

Challenge and get performance evaluation