Fundamentals of Cloud IoT Edge ML Assignment 1 Answers

Fundamentals of Cloud IoT Edge ML Assignment 2 Answers

Fundamentals of Cloud IoT Edge ML Assignment 3 Answers

Fundamentals of Cloud IoT Edge ML Assignment 3 Answers

1) List out the limitations of traditional IoT platform.

• Poor internet connectivity
• Poor data gravity
• Poor real time responses
• All of the above

Answer: All of the above

2) ______ is the edge computing approach that significantly saves the bandwidth and cloud storage.

• Filtered data transfer
• Faster decision-making
• Both of them
• None of them

Answer: Filtered data transfer

3) In the _______ phase, a developer feeds their model a curated dataset so that it can “learn” everything it needs to about the type of data it will analyze. Then, in the _________ phase, the model can make predictions based on live data to produce actionable results.

• Training, Inferencing
• Training, Model shifting
• Model shifting, Inferencing
• Model shifting, Training

Answer: Training, Inferencing

4) ________  involves calculating explicit label for every data point in the sample based on the actual observations on the data.

• Data preparation
• Data collection
• Data streaming
• None of the above

Answer: Data preparation

5. List out the key characteristics of Azure IoT Hub.

• Manages service for bi-directional communication
• Platform as a service
• Programmable SDK
• All of the above

Answer: All of the above

6. Which of the following studies various techniques to classify patterns?

• Image Processing
• Photogrammetry
• Image Recognition
• Pattern Recognition

Answer: Pattern Recognition

7. The input and output of image processing are?

• Signal and image
• Signal only
• Image only
• Depends on input

Answer: Depends on input

8. In Fast R-CNN, we extract feature maps from the input image only once as compared to R-CNN where we extract feature maps from each region proposal separately?

• True
• False

Answer: True

9. Which of the following networks has the fastest prediction time?

• R-CNN
• Fast R-CNN
• Faster R-CNN

Answer: Faster R-CNN

10. List out the features provided by Azure Custom Vision service:

• Train a computer vision model by simply uploading and labeling few images.
• Build image classifier model using code-free and code-first approach.
• Deploy the model in the cloud on-premise, or on edge devices.
• All of the above

Answer: TAll of the above

Disclaimer: Chandras EDU does not guarantee the correctness of the answers. These answers are based on the data provided by the NPTEL video lectures, are just for reference, and request students to complete the assignments independently.

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