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2020/Feb New Braindump2go AI-100 Exam Dumps with PDF and VCE Free Updated

February 26, 2020

February/2020 Braindump2go AI-100 Exam Dumps with PDF and VCE New Updated Today! Following are some new AI-100 Exam Questions,



New Question
Drag and Drop Question
You are designing an AI solution that will use IoT devices to gather data from conference attendees, and then later analyze the data. The IoT devices will connect to an Azure IoT hub.
You need to design a solution to anonymize the data before the data is sent to the IoT hub.
Which three actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
  image
Answer:
  image

Explanation:
Step 1: Create a storage container
ASA Edge jobs run in containers deployed to Azure IoT Edge devices.
Step 2: Create an Azure Stream Analytics Edge Job
Azure Stream Analytics (ASA) on IoT Edge empowers developers to deploy near-real-time analytical intelligence closer to IoT devices so that they can unlock the full value of device-generated data.
Scenario overview:
  image
Step 3: Add the job to the IoT devices in IoT
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-edge


New Question
Hotspot Question
You are developing an application that will perform clickstream analysis.
The application will ingest and analyze millions of messages in the real time.
You need to ensure that communication between the application and devices is bidirectional.
What should you use for data ingestion and stream processing? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
  image
Answer:
  image
Explanation:
Box 1: Azure IoT Hub
Azure IoT Hub is the cloud gateway that connects IoT devices to gather data and drive business insights and automation. In addition, IoT Hub includes features that enrich the relationship between your devices and your backend systems. Bi-directional communication capabilities mean that while you receive data from devices you can also send commands and policies back to devices. Note on why not Azure Event Hubs: An Azure IoT Hub contains an Event Hub and hence essentially is an Event Hub plus additional features. An important additional feature is that an Event Hub can only receive messages, whereas an IoT Hub additionally can also send messages to individual devices. Further, an Event Hub has access security on hub level, whereas an IoT Hub is aware of the individual devices and can grand and revoke access on device level. Box 2: Azure Hdinsight with Azure Machine Learning service References:
https://docs.microsoft.com/en-us/azure/iot-hub/iot-hub-compare-event-hubs https://docs.microsoft.com/en-us/azure/hdinsight/hdinsight-machine-learning-overview


New Question
Drag and Drop Question
You develop a custom application that uses a token to connect to Azure Cognitive Services resources.
A new security policy requires that all access keys are changed every 30 days.
You need to recommend a solution to implement the security policy.
Which three actions should you recommend be performed every 30 days? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.
  image
Answer:
  image
Explanation:
Step 1: Generate new keys in the Cognitive Service resources
  image
Step 2: Retrieve a token from the Cognitive Services endpoint Step 3: Update the custom application to use the new authorization Each request to an Azure Cognitive Service must include an authentication header. This header passes along a subscription key or access token, which is used to validate your subscription for a service or group of services.
References:
https://docs.microsoft.com/en-us/azure/cognitive-services/authentication


New Question
Drag and Drop Question
You use an Azure key vault to store credentials for several Azure Machine Learning applications.
You need to configure the key vault to meet the following requirements:
– Ensure that the IT security team can add new passwords and periodically change the passwords.
– Ensure that the applications can securely retrieve the passwords for the applications.
– Use the principle of least privilege.
Which permissions should you grant? To answer, drag the appropriate permissions to the correct targets. Each permission may be used once, more than once, or not at all. You may need to drag the split bar between panes or scroll to view content.
NOTE: Each correct selection is worth one point.
  image
Answer:
  image
Explanation:
Incorrect Answers:
Not Keys as they are used for encryption only.
References:
https://docs.microsoft.com/en-us/azure/key-vault/key-vault-secure-your-key-vault


New Question
Your company is building custom models that integrate into microservices architecture on Azure Kubernetes Services (AKS).
The model is built by using Python and published to AKS.
You need to update the model and enable Azure Application Insights for the model.
What should you use?


A.    the Azure CLI
B.    MLNET Model Builder
C.    the Azure Machine Learning SDK
D.    the Azure portal


Answer: C
Explanation:
You can set up Azure Application Insights for Azure Machine Learning. Application Insights gives you the opportunity to monitor:
Request rates, response times, and failure rates.
Dependency rates, response times, and failure rates.
Exceptions.
Requirements include an Azure Machine Learning workspace, a local directory that contains your scripts, and the Azure Machine Learning SDK for Python installed.
References:
https://docs.microsoft.com/bs-latn-ba/azure/machine-learning/service/how-to-enable-app-insights


New Question
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 are developing an application that uses an Azure Kubernetes Service (AKS) cluster.
You are troubleshooting a node issue.
You need to connect to an AKS node by using SSH.
Solution: You run the kubect1 command, and then you create an SSH connection.
Does this meet the goal?


A.    Yes
B.    No


Answer: B


New Question
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 an app named App1 that uses the Face API.
App1 contains several PersonGroup objects.
You discover that a PersonGroup object for an individual named Ben Smith cannot accept additional entries. The PersonGroup object for Ben Smith contains 10,000 entries.
You need to ensure that additional entries can be added to the PersonGroup object for Ben Smith. The solution must ensure that Ben Smith can be identified by all the entries.
Solution: You modify the custom time interval for the training phase of App1.
Does this meet the goal?


A.    Yes
B.    No


Answer: B
Explanation:
Instead, use a LargePersonGroup. LargePersonGroup and LargeFaceList are collectively referred to as large-scale operations. LargePersonGroup can contain up to 1 million persons, each with a maximum of 248 faces. LargeFaceList can contain up to 1 million faces. The large-scale operations are similar to the conventional PersonGroup and FaceList but have some differences because of the new architecture.
References:
https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/how-to-use-large-scale


New Question
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 an app named App1 that uses the Face API.
App1 contains several PersonGroup objects.
You discover that a PersonGroup object for an individual named Ben Smith cannot accept additional entries. The PersonGroup object for Ben Smith contains 10,000 entries.
You need to ensure that additional entries can be added to the PersonGroup object for Ben Smith. The solution must ensure that Ben Smith can be identified by all the entries.
Solution: You create a second PersonGroup object for Ben Smith.
Does this meet the goal?


A.    Yes
B.    No


Answer: B
Explanation:
Instead, use a LargePersonGroup. LargePersonGroup and LargeFaceList are collectively referred to as large-scale operations. LargePersonGroup can contain up to 1 million persons, each with a maximum of 248 faces. LargeFaceList can contain up to 1 million faces. The large-scale operations are similar to the conventional PersonGroup and FaceList but have some differences because of the new architecture.
References:
https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/how-to-use-large-scale


New Question
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 an app named App1 that uses the Face API.
App1 contains several PersonGroup objects.
You discover that a PersonGroup object for an individual named Ben Smith cannot accept additional entries. The PersonGroup object for Ben Smith contains 10,000 entries.
You need to ensure that additional entries can be added to the PersonGroup object for Ben Smith. The solution must ensure that Ben Smith can be identified by all the entries.
Solution: You migrate all the entries to the LargePersonGroup object for Ben Smith.
Does this meet the goal?


A.    Yes
B.    No


Answer: A
Explanation:
LargePersonGroup and LargeFaceList are collectively referred to as large-scale operations.
LargePersonGroup can contain up to 1 million persons, each with a maximum of 248 faces. LargeFaceList can contain up to 1 million faces. The large-scale operations are similar to the conventional PersonGroup and FaceList but have some differences because of the new architecture.
References:
https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/how-to-use-large-scale


New Question
Your company plans to develop a mobile app to provide meeting transcripts by using speech-to-text. Audio from the meetings will be streamed to provide real-time transcription.
You need to recommend which task each meeting participant must perform to ensure that the transcripts of the meetings can identify all participants.
Which task should you recommend?


A.    Record the meeting as an MP4.
B.    Create a voice signature.
C.    Sign up for Azure Speech Services.
D.    Sign up as a guest in Azure Active Directory (Azure AD)


Answer: B
Explanation:
The first step is to create voice signatures for the conversation participants. Creating voice signatures is required for efficient speaker identification.
Note: In addition to the standard baseline model used by the Speech Services, you can customize models to your needs with available data, to overcome speech recognition barriers such as speaking style, vocabulary and background noise.
References:
https://docs.microsoft.com/bs-latn-ba/azure/cognitive-services/speech-service/how-to-use-conversation-transcription-service


New Question
You need to create a prototype of a bot to demonstrate a user performing a task. The demonstration will use the Bot Framework Emulator.
Which botbuilder CLI tool should you use to create the prototype?


A.    Chatdown
B.    QnAMaker
C.    Dispatch
D.    LuDown


Answer: A
Explanation:
Use Chatdown to produce prototype mock conversations in markdown and convert the markdown to transcripts you can load and view in the new V4 Bot Framework Emulator.
Incorrect Answers:
B: QnA Maker is a cloud-based API service that lets you create a conversational question-and-answer layer over your existing data. Use it to build a knowledge base by extracting questions and answers from your semi-structured content, including FAQs, manuals, and documents. Answer users’ questions with the best answers from the QnAs in your knowledge base–automatically. Your knowledge base gets smarter, too, as it continually learns from user behavior.
C: Dispatch lets you build language models that allow you to dispatch between disparate components (such as QnA, LUIS and custom code).
D: LuDown build LUIS language understanding models using markdown files
References:
https://github.com/microsoft/botframework/blob/master/README.md


New Question
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?


A.    Face API and Text Analytics
B.    Computer Vision and Text Analytics
C.    QnA Maker and Computer Vision
D.    Speech to Text and Face API


Answer: D
Explanation:
Speech-to-text from Azure Speech Services, also known as speech-to-text, enables real-time transcription of audio streams into text that your applications, tools, or devices can consume, display, and take action on as command input.
Face detection: Detect one or more human faces in an image and get back face rectangles for where in the image the faces are, along with face attributes which contain machine learning-based predictions of facial features. The face attribute features available are: Age, Emotion, Gender, Pose, Smile, and Facial Hair along with 27 landmarks for each face in the image.
References:
https://docs.microsoft.com/en-us/azure/cognitive-services/speech-service/speech-to-text https://azure.microsoft.com/en-us/services/cognitive-services/face/


New Question
You need to evaluate trends in fuel prices during a period of 10 years. The solution must identify unusual fluctuations in prices and produce visual representations.
Which Azure Cognitive Services API should you use?


A.    Anomaly Detector
B.    Computer Vision
C.    Text Analytics
D.    Bing Autosuggest


Answer: A
Explanation:
The Anomaly Detector API enables you to monitor and detect abnormalities in your time series data with machine learning. The Anomaly Detector API adapts by automatically identifying and applying the best- fitting models to your data, regardless of industry, scenario, or data volume. Using your time series data, the API determines boundaries for anomaly detection, expected values, and which data points are anomalies.
References:
https://docs.microsoft.com/en-us/azure/cognitive-services/anomaly-detector/overview


New Question
You plan to perform analytics of the medical records of patients located around the world.
You need to recommend a solution that avoids storing and processing data in the cloud.
What should you include in the recommendation?


A.    Azure Machine Learning Studio
B.    the Text Analytics API that has container support
C.    Azure Machine Learning services
D.    an Apache Spark cluster that uses MMLSpark


Answer: D
Explanation:
The Microsoft Machine Learning Library for Apache Spark (MMLSpark) assists in provisioning scalable machine learning models for large datasets, especially for building deep learning problems. MMLSpark works with SparkML pipelines, including Microsoft CNTK and the OpenCV library, which provide end-to- end support for the ingress and processing of image input data, categorization of images, and text analytics using pre-trained deep learning algorithms.
References:
https://subscription.packtpub.com/book/big_data_and_business_intelligence/9781789131956/10/ ch10lvl1sec61/an-overview-of-the-microsoft-machine-learning-library-for-apache-spark-mmlspark



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