Free Microsoft AI-100 Exam Dumps Questions & Answers

You are designing a Custom Vision Service solution to identify fresh produce in grocery stores. The solution will be deployed as part of a mobile app.
You need to recommend the configurations for the Custom Vision API. The solution must minimize the size of the mobile app.
What should you recommend? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.

Correct Answer:

Explanation

Box 1:
Project type: Classification
Box 2:
Domain: Food (compact)
If you want to classify photographs of individual fruits or vegetables, use the Food domain. Compact domains are optimized for the constraints of real-time classification on mobile devices.
Box 3:
Export capability: Vision AI Dev Kit
Custom Vision Service supports the following exports:
* Tensorflow for Android.
* CoreML for iOS11.
* ONNX for Windows ML.
* Vision AI Developer Kit.
* A Docker container for Windows, Linux, or ARM architecture.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/select-domain
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/export-your-model

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.

Correct Answer:

Explanation

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/

You have an Azure Machine Learning model that is deployed to a web service.
You plan to publish the web service by using the name ml.contoso.com.
You need to recommend a solution to ensure that access to the web service is encrypted.
Which three actions should you recommend? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

• A.  Create an Azure Key Vault
• B.  Generate a shared access signature (SAS)
• C.  Update the web service
• D.  Add a deployment slot
• E.  Update DNS
• F.  Obtain an SSL certificate

You need to build an A) solution that will be shared between several developers and customers.
You plan to write code, host code, and document the runtime all within a single user experience.
You build the environment to host the solution.
Which three actions should you perform in sequence next? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Correct Answer:

Explanation

Step 1: Create an Azure Machine Learning Studio workspace
Step 2: Create a notebook
You can manage notebooks using the UI, the CLI, and by invoking the Workspace API.
To create a notebook
* Click the Workspace button Workspace Icon or the Home button Home Icon in the sidebar. Do one of the following:
Next to any folder, click the Menu Dropdown on the right side of the text and select Create > Notebook.
Create Notebook
In the Workspace or a user folder, click Down Caret and select Create > Notebook.
2. In the Create Notebook dialog, enter a name and select the notebook's primary language.
3. If there are running clusters, the Cluster drop-down displays. Select the cluster to attach the notebook to.
4. Click Create.
Step 3: Create a new experiment
Create a new experiment by clicking +NEW at the bottom of the Machine Learning Studio window. Select EXPERIMENT > Blank Experiment.
References:
https://docs.azuredatabricks.net/user-guide/notebooks/notebook-manage.html
https://docs.microsoft.com/en-us/azure/machine-learning/service/quickstart-run-cloud-notebook

Which two services should be implemented so that Butler can find available rooms based on the technical requirements? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.

• A.  Content Moderator
• B.  Azure Search
• C.  Language Understanding (LUIS)
• D.  Bing Entity Search
• E.  QnA Maker