Practice Libraries (3.5) - AI for Edge Devices and Internet of Things - Artificial Intelligence Advance

Practice: Libraries

Lesson 3.5AI for Edge Devices and Internet of Things

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9 questions

Flashcard drill
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.
Name one library used for edge AI deployments.
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Think about lightweight frameworks.
Question 2.
What does quantization do?
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It involves lowering the bit size of weights.
3Question 3.
Which of the following is an advantage of TensorFlow Lite?
- High computational requirements
- Optimized for mobile
- Limited functionalities
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Think about the main purpose of this framework.
4Question 4.
True or False: ONNX Runtime can only run models trained in PyTorch.
- True
- False
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Consider the versatility of ONNX.
Question 5.
Design a mobile app that leverages TensorFlow Lite for a specific health monitoring function. Detail the rationale for your design choices, including how you would handle model optimization.
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Consider the balance between accuracy and resource use.
Question 6.
Discuss the potential challenges faced when deploying models using ONNX Runtime across different platforms and propose solutions.
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Think about what factors could influence cross-platform compatibility.

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