Practice Model Serving Architectures (12.6.1) - Scalability & Systems - Advance Machine Learning
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Model Serving Architectures

Practice - Model Serving Architectures

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Practice Questions

Test your understanding with targeted questions

Question 1 Easy

What is batch inference?

💡 Hint: Think about processing data in larger groups or sets.

Question 2 Easy

Name one tool used for TensorFlow model serving.

💡 Hint: This tool shares part of its name with its creator.

4 more questions available

Interactive Quizzes

Quick quizzes to reinforce your learning

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

💡 Hint: Think about timing — does it wait for all data?

Question 2

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

True
False

💡 Hint: Consider applications like chatbots.

1 more question available

Challenge Problems

Push your limits with advanced challenges

Challenge 1 Hard

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?

💡 Hint: Consider user experience for both timely and comprehensive data insights.

Challenge 2 Hard

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

💡 Hint: Consider the urgency vs. depth of feedback needed.

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