Microsoft Designing and Implementing an Azure AI Solution - AI-100 FREE EXAM DUMPS QUESTIONS & ANSWERS
You need to recommend a data storage solution that meets the technical requirements.
What is the best data storage solution to recommend? More than one answer choice may achieve the goal.
Select the BEST answer.
What is the best data storage solution to recommend? More than one answer choice may achieve the goal.
Select the BEST answer.
Correct Answer: D
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You plan to deploy Azure loT Edge devices that will each store more than 10,000 images locally and classify the images by using a Custom Vision Service classifier. Each image is approximately 5 MB.
You need to ensure that the images persist on the devices for 14 days.
What should you use?
You need to ensure that the images persist on the devices for 14 days.
What should you use?
Correct Answer: C
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You plan to create an intelligent bot to handle internal user chats to the help desk of your company. The bot has the following requirements:
* Must be able to interpret what a user means.
* Must be able to perform multiple tasks for a user.
* Must be able to answer questions from an existing knowledge base
You need to recommend which solutions meet the requirements.
Which solution should you recommend for each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
* Must be able to interpret what a user means.
* Must be able to perform multiple tasks for a user.
* Must be able to answer questions from an existing knowledge base
You need to recommend which solutions meet the requirements.
Which solution should you recommend for each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation
Box 1: The Language Understanding (LUIS) service
Language Understanding (LUIS) is a cloud-based API service that applies custom machine-learning intelligence to a user's conversational, natural language text to predict overall meaning, and pull out relevant, detailed information.
Box 2: Text Analytics API
The Text Analytics API is a cloud-based service that provides advanced natural language processing over raw text, and includes four main functions: sentiment analysis, key phrase extraction, named entity recognition, and language detection.
Box 3: The QnA Maker service
QnA Maker is a cloud-based Natural Language Processing (NLP) service that easily creates a natural conversational layer over your data. It can be used to find the most appropriate answer for any given natural language input, from your custom knowledge base (KB) of information.
Reference:
https://docs.microsoft.com/en-us/azure/bot-service/bot-builder-tutorial-dispatch
https://docs.microsoft.com/en-us/azure/cognitive-services/qnamaker/overview/overview
Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have Azure IoT Edge devices that generate streaming data.
On the devices, you need to detect anomalies in the data by using Azure Machine Learning models. Once an anomaly is detected, the devices must add information about the anomaly to the Azure IoT Hub stream.
Solution: You deploy an Azure Machine Learning model as an IoT Edge module.
Does this meet the goal?
After you answer a question, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You have Azure IoT Edge devices that generate streaming data.
On the devices, you need to detect anomalies in the data by using Azure Machine Learning models. Once an anomaly is detected, the devices must add information about the anomaly to the Azure IoT Hub stream.
Solution: You deploy an Azure Machine Learning model as an IoT Edge module.
Does this meet the goal?
Correct Answer: B
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Your company manages a sports team.
The company sets up a video booth to record messages for the team.
Before replaying the messages on a video screen, you need to generate captions for the messages and check the emotions in the video to ensure that only positive messages are played.
Which Azure Cognitive Services service should you use?
The company sets up a video booth to record messages for the team.
Before replaying the messages on a video screen, you need to generate captions for the messages and check the emotions in the video to ensure that only positive messages are played.
Which Azure Cognitive Services service should you use?
Correct Answer: C
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Note: This question is part of a series of questions that present the same scenario. Each question in the series contains a unique solution that might meet the stated goals. Some question sets might have more than one correct solution, while others might not have a correct solution.
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You create several Al models in Azure Machine Learning Studio.
You deploy the models to a production environment.
You need to monitor the compute performance of the models.
Solution: You enable AppInsights diagnostics.
Does this meet the goal?
After you answer a question in this section, you will NOT be able to return to it. As a result, these questions will not appear in the review screen.
You create several Al models in Azure Machine Learning Studio.
You deploy the models to a production environment.
You need to monitor the compute performance of the models.
Solution: You enable AppInsights diagnostics.
Does this meet the goal?
Correct Answer: A
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You are developing a mobile application that will perform optical character recognition (OCR) from photos.
The application will annotate the photos by using metadata, store the photos in Azure Blob storage, and then score the photos by using an Azure Machine Learning model.
What should you use to process the data?
The application will annotate the photos by using metadata, store the photos in Azure Blob storage, and then score the photos by using an Azure Machine Learning model.
What should you use to process the data?
Correct Answer: D
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You have an Azure SQL database, an Azure Data Lake Storage Gen 2 account, and an API developed by using Azure Machine Learning Studio.
You need to ingest data once daily from the database. score each row by using the API, and write the data to the storage account.
Solution: You create an Azure Data Factory pipeline that contains a Jupyter notebook activity.
Does this meet the goal?
You need to ingest data once daily from the database. score each row by using the API, and write the data to the storage account.
Solution: You create an Azure Data Factory pipeline that contains a Jupyter notebook activity.
Does this meet the goal?
Correct Answer: A
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You are designing an AI solution that will provide feedback to teachers who train students over the Internet.
The students will be in classrooms located in remote areas. The solution will capture video and audio data of the students in the classrooms.
You need to recommend Azure Cognitive Services for the AI solution to meet the following requirements:
Alert teachers if a student facial expression indicates the student is angry or scared.
Identify each student in the classrooms for attendance purposes.
Allow the teachers to log voice conversations as text.
Which Cognitive Services should you recommend?
The students will be in classrooms located in remote areas. The solution will capture video and audio data of the students in the classrooms.
You need to recommend Azure Cognitive Services for the AI solution to meet the following requirements:
Alert teachers if a student facial expression indicates the student is angry or scared.
Identify each student in the classrooms for attendance purposes.
Allow the teachers to log voice conversations as text.
Which Cognitive Services should you recommend?
Correct Answer: B
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You are designing an Azure infrastructure to support an Azure Machine Learning solution that will have multiple phases. The solution must meet the following requirements:
* Securely query an on-premises database once a week to update product lists.
* Access the data without using a gateway.
* Orchestrate the separate phases.
What should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
* Securely query an on-premises database once a week to update product lists.
* Access the data without using a gateway.
* Orchestrate the separate phases.
What should you use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Correct Answer:
Explanation
Box 1: Azure App Service Hybrid Connections
With Hybrid Connections, Azure websites and mobile services can access on-premises resources as if they were located on the same private network. Application admins thus have the flexibility to simply lift-and-shift specific most front-end tiers to Azure with minimal configuration changes, extending their enterprise apps for hybrid scenarios.
Incorrect Answer: The VPN connection solution both use gateways.
Box 2: Machine Learning pipelines
Typically when running machine learning algorithms, it involves a sequence of tasks including pre-processing, feature extraction, model fitting, and validation stages. For example, when classifying text documents might involve text segmentation and cleaning, extracting features, and training a classification model with cross-validation. Though there are many libraries we can use for each stage, connecting the dots is not as easy as it may look, especially with large-scale datasets. Most ML libraries are not designed for distributed computation or they do not provide native support for pipeline creation and tuning.
Box 3: Azure Databricks
References:
https://azure.microsoft.com/is-is/blog/hybrid-connections-preview/
https://databricks.com/glossary/what-are-ml-pipelines