Practice Model Serving Architectures - 12.6.1 | 12. Scalability & Systems | Advance Machine Learning
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Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is batch inference?

πŸ’‘ Hint: Think about processing data in larger groups or sets.

Question 2

Easy

Name one tool used for TensorFlow model serving.

πŸ’‘ Hint: This tool shares part of its name with its creator.

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 main purpose of batch inference?

  • To process data as it arrives
  • To make predictions on a set of data at once
  • To manage incoming data streams

πŸ’‘ Hint: Think about timing β€” does it wait for all data?

Question 2

True or False: Real-time inference is ideal for scenarios requiring immediate predictions.

  • True
  • False

πŸ’‘ Hint: Consider applications like chatbots.

Solve 1 more question and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Design a model-serving architecture for a personalized news feed application that requires both batch and real-time predictions. What types of inferences would you utilize, and why?

πŸ’‘ Hint: Consider user experience for both timely and comprehensive data insights.

Question 2

Evaluate the trade-offs of using batch inference versus real-time inference in a streaming video analytics application.

πŸ’‘ Hint: Consider the urgency vs. depth of feedback needed.

Challenge and get performance evaluation