Practice Deployment and Serving Models - 3 | AI Integration in Real-World Systems and Enterprise Solutions | Artificial Intelligence Advance
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3 - Deployment and Serving Models

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Learning

Practice Questions

Test your understanding with targeted questions related to the topic.

Question 1

Easy

What is batch inference?

💡 Hint: Think about when you would want to analyze data rather than act on it immediately.

Question 2

Easy

What does real-time inference provide?

💡 Hint: Consider scenarios where you need quick responses.

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?

  • Random predictions
  • Scheduled model runs
  • Real-time analysis

💡 Hint: Think of when you would want to analyze data over time.

Question 2

Is real-time inference important for critical applications like fraud detection?

  • True
  • False

💡 Hint: Consider the consequences of delay in serious matters.

Solve 2 more questions and get performance evaluation

Challenge Problems

Push your limits with challenges.

Question 1

Compare the advantages and disadvantages of deploying a model using batch inference versus edge deployment in terms of scalability and use-case effectiveness.

💡 Hint: Think about scenarios where immediate results are mission-critical versus those where thorough analysis is required.

Question 2

Design a workflow for an AI application that utilizes both real-time inference and batch processing, emphasizing touchpoints and data transitions between the two methods.

💡 Hint: Consider how interactions feed into different segments of processing for deeper insights.

Challenge and get performance evaluation