Microsoft AI-100 Exam Practice Questions (P. 3)
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Question #14
HOTSPOT -
You are designing an AI solution that will be used to find buildings in aerial pictures.
Users will upload the pictures to an Azure Storage account. A separate JSON document will contain for the pictures.
The solution must meet the following requirements:
✑ Store metadata for the pictures in a data store.
✑ Run a custom vision Azure Machine Learning module to identify the buildings in a picture and the position of the buildings' edges.
✑ Run a custom mathematical module to calculate the dimensions of the buildings in a picture based on the metadata and data from the vision module.
You need to identify which Azure infrastructure services are used for each component of the AI workflow. The solution must execute as quickly as possible.
What should you identify? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
You are designing an AI solution that will be used to find buildings in aerial pictures.
Users will upload the pictures to an Azure Storage account. A separate JSON document will contain for the pictures.
The solution must meet the following requirements:
✑ Store metadata for the pictures in a data store.
✑ Run a custom vision Azure Machine Learning module to identify the buildings in a picture and the position of the buildings' edges.
✑ Run a custom mathematical module to calculate the dimensions of the buildings in a picture based on the metadata and data from the vision module.
You need to identify which Azure infrastructure services are used for each component of the AI workflow. The solution must execute as quickly as possible.
What should you identify? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Hot Area:
Correct Answer:
Box 1: Azure Blob Storage -
Containers and blobs support custom metadata, represented as HTTP headers.
Box 2: NV -
The NV-series enables powerful remote visualisation workloads and other graphics-intensive applications backed by the NVIDIA Tesla M60 GPU.
Note: The N-series is a family of Azure Virtual Machines with GPU capabilities. GPUs are ideal for compute and graphics-intensive workloads, helping customers to fuel innovation through scenarios like high-end remote visualisation, deep learning and predictive analytics.
Box 3: F -
F-series VMs feature a higher CPU-to-memory ratio. Example use cases include batch processing, web servers, analytics and gaming.
Incorrect:
A-series VMs have CPU performance and memory configurations best suited for entry level workloads like development and test.
References:
https://azure.microsoft.com/en-in/pricing/details/virtual-machines/series/
Box 1: Azure Blob Storage -
Containers and blobs support custom metadata, represented as HTTP headers.
Box 2: NV -
The NV-series enables powerful remote visualisation workloads and other graphics-intensive applications backed by the NVIDIA Tesla M60 GPU.
Note: The N-series is a family of Azure Virtual Machines with GPU capabilities. GPUs are ideal for compute and graphics-intensive workloads, helping customers to fuel innovation through scenarios like high-end remote visualisation, deep learning and predictive analytics.
Box 3: F -
F-series VMs feature a higher CPU-to-memory ratio. Example use cases include batch processing, web servers, analytics and gaming.
Incorrect:
A-series VMs have CPU performance and memory configurations best suited for entry level workloads like development and test.
References:
https://azure.microsoft.com/en-in/pricing/details/virtual-machines/series/
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