[December-2019-New]Braindump2go AI-100 VCE and PDF Dumps Free Download

December/2019 Braindump2go AI-100 Dumps with PDF and VCE New Updated Today! Following are some new AI-100 Exam Questions,

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 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 Azure Stream Analytics as an IoT Edge module.
Does this meet the goal?

A. Yes
B. No

Answer: A
Explanation:
Available in both the cloud and Azure IoT Edge, Azure Stream Analytics offers built-in machine learning based anomaly detection capabilities that can be used to monitor the two most commonly occurring anomalies: temporary and persistent.
Stream Analytics supports user-defined functions, via REST API, that call out to Azure Machine Learning endpoints.
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-machine-learning-anomaly-detection

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 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 expose a Machine Learning model as an Azure web service.
Does this meet the goal?

A. Yes
B. No

Answer: B
Explanation:
Instead use Azure Stream Analytics and REST API.
Note. Available in both the cloud and Azure IoT Edge, Azure Stream Analytics offers built-in machine learning based anomaly detection capabilities that can be used to monitor the two most commonly occurring anomalies: temporary and persistent.
Stream Analytics supports user-defined functions, via REST API, that call out to Azure Machine Learning endpoints.
References:
https://docs.microsoft.com/en-us/azure/stream-analytics/stream-analytics-machine-learning-anomaly-detection

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 create several AI 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 write a custom scoring script.
Does this meet the goal?

A. Yes
B. No

Answer: B
Explanation:
You need to enable Model data collection.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-enable-data-collection

New Question
Your company has recently purchased and deployed 25,000 IoT devices.
You need to recommend a data analysis solution for the devices that meets the following requirements:
– Each device must use its own credentials for identity.
– Each device must be able to route data to multiple endpoints.
The solution must require the minimum amount of customized code.
What should you include in the recommendation?

A. Microsoft Azure Notification Hubs
B. Microsoft Azure Event Hubs
C. Microsoft Azure IoT Hub
D. Microsoft Azure Service Bus

Answer: C
Explanation:
An IoT hub has a default built-in endpoint. You can create custom endpoints to route messages to by linking other services in your subscription to the hub. Individual devices connect using credentials stored in the IoT hub’s identity registry.
References:
https://docs.microsoft.com/en-us/azure/iot-hub/iot-hub-devguide-security

New Question
A data scientist deploys a deep learning model on an Fsv2 virtual machine.
Data analysis is slow.
You need to recommend which virtual machine series the data scientist must use to ensure that data analysis occurs as quickly as possible.
Which series should you recommend?

A. ND
B. B
C. DC
D. Ev3

Answer: A
Explanation:
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. The ND-series is focused on training and inference scenarios for deep learning. It uses the NVIDIA Tesla P40 GPUs. The latest version – NDv2 – features the NVIDIA Tesla V100 GPUs.
References:
https://azure.microsoft.com/en-in/pricing/details/virtual-machines/series/

New Question
You have Azure IoT Edge devices that generate measurement data from temperature sensors. The data changes very slowly.
You need to analyze the data in a temporal two-minute window. If the temperature rises five degrees above a limit, an alert must be raised.
The solution must minimize the development of custom code.
What should you use?

A. A Machine Learning model as a web service
B. an Azure Machine Learning model as an IoT Edge module
C. Azure Stream Analytics as an IoT Edge module
D. Azure Functions as an IoT Edge module

Answer: C
Explanation:
https://docs.microsoft.com/en-us/azure/iot-edge/tutorial-deploy-stream-analytics

New Question
You need to configure versioning and logging for Azure Machine Learning models.
Which Machine Learning service application should you use?

A. models
B. activities
C. experiments
D. pipelines
E. deployments

Answer: E
Explanation:
https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-enable-logging#logging-for-deployed-models

New Question
Your company has 1,000 AI developers who are responsible for provisioning environments in Azure. You need to control the type, size, and location of the resources that the developers can provision.
What should you use?

A. Azure Key Vault
B. Azure service principals
C. Azure managed identities
D. Azure Security Center
E. Azure Policy

Answer: B
Explanation:
When an application needs access to deploy or configure resources through Azure Resource Manager in Azure Stack, you create a service principal, which is a credential for your application. You can then delegate only the necessary permissions to that service principal.
References:
https://docs.microsoft.com/en-us/azure/azure-stack/azure-stack-create-service-principals

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 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 Applnsights diagnostics.
Does this meet the goal?

A. Yes
B. No

Answer: B
Explanation:
You need to enable Model data collection.
References:
https://docs.microsoft.com/en-us/azure/machine-learning/service/how-to-enable-data-collection

New Question
Drag and Drop Question
You are designing an Azure Batch Al solution that will be used to train many different Azure Machine Learning models. The solution will perform the following:
– Image recognition
– Deep learning that uses convolutional neural networks
You need to select a compute infrastructure for each model. The solution must minimize the processing time.
What should you use for each model? To answer, drag the appropriate compute infrastructures to the correct models. Each compute infrastructure 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.

Answer:

New Question
Hotspot Question
You plan to deploy an application that will perform image recognition. The application will store image data in two Azure Blob storage stores named Blob! and Blob2.
You need to recommend a security solution that meets the following requirements:
– Access to Blobl must be controlled by a using a role.
– Access to Blob2 must be time-limited and constrained to specific operations.
What should you recommend using to control access to each blob store? To answer, select the appropriate options in the answer area. NOTE: Each correct selection is worth one point.

Answer:

Explanation:
https://docs.microsoft.com/en-us/azure/storage/common/storage-auth

1.|2019 Latest Braindump2go AI-100 Exam Dumps (VCE & PDF) Instant Download:

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2.|2019 Latest Braindump2go AI-100 Exam Questions & Answers Instant Download:

https://drive.google.com/drive/folders/16bPnYGUoXhAsx9eAI8URN71n7ufNMWaM?usp=sharing

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