Practice Deployment (30.4.4) - Introduction to Machine Learning and AI

Practice: Deployment

Lesson 30.4.4Introduction to Machine Learning and AI

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9 questions

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4 cards from this section. Quick, good the night before a test.
Exercise
6 questions · about 4 min · pass mark 70%. Hints available.
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Quiz
3 questions · about 2 min · pass mark 70%. Hints available.
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6 sample questions

Question 1.
What does deployment mean in machine learning?
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Think about how a model can be put to use.
Question 2.
Name the two primary methods of deployment discussed.
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One is on-site, the other relies on remote servers.
3Question 3.
What is the primary focus of deployment in machine learning?
- Integration of models into applications
- Training models
- Data collection
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Think about what happens after a model is trained.
4Question 4.
True or False: Real-time predictions can be made by both embedded and cloud approaches.
- True
- False
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Consider the capabilities of both deployment strategies.
Question 5.
Consider a construction site where real-time monitoring is critical. Develop a complete deployment plan for a predictive maintenance model, detailing the model's interaction with the embedded system and the cloud.
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Think about the advantages of using both embedded and cloud solutions.
Question 6.
Analyze the trade-offs of using embedded versus cloud-based deployment for a machine learning model used in traffic management in urban infrastructure.
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Consider the demands of real-time vs. extensive data handling.

5 more questions in this section. Enroll free to practise them all.