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NEW QUESTION: 1
The Supplier Analysis report shows Year to Date information that is inaccurate. Why is this so?
A. The aging accounts are not set up in the A/P Constants.
B. Your Data Selection in the Supplier Master report is incorrect.
C. The Beginning Year A/P and A/P period fields have not been updated In the Company Numbers and Names.
D. The Supplier/Customer Totals by G/L Accounts report has not been run.
E. The AP Annual Close has not been processed.
Answer: B
NEW QUESTION: 2
Your company plans to deploy several apps that will use Azure Cognitive Services APIs.
You need to recommend which Cognitive Services APIs must be used to meet the following requirements:
* Must be able to identify inappropriate text and profanities in multiple languages.
* Must be able to interpret user requests sent by using text input.
* Must be able to identify named entities in text.
Which API should you recommend for each requirement? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation
Box 1: Content Moderator
The Azure Content Moderator API is a cognitive service that checks text, image, and video content for material that is potentially offensive, risky, or otherwise undesirable. When such material is found, the service applies appropriate labels (flags) to the content. Your app can then handle flagged content in order to comply with regulations or maintain the intended environment for users.
Box 2: Language Understanding (LUIS)
Designed to identify valuable information in conversations, LUIS interprets user goals (intents) and distills valuable information from sentences (entities), for a high quality, nuanced language model. LUIS integrates seamlessly with the Azure Bot Service, making it easy to create a sophisticated bot.
Box 3: Text Analytics
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.
References:
https://docs.microsoft.com/bs-latn-ba/azure/cognitive-services/content-moderator/overview
https://www.luis.ai/home
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/
NEW QUESTION: 3
A space exploration company owns a series of telescopes that capture a large number of images and data of the night sky. The images and data are processed on an application hosted on AWS Fargate in a target group assigned to an Application Load Balancer (ALB). The application is made available through the address https
/'space example com
Scientists require another custom-built application hosted on several Amazon EC2 instances within an Auto Scaling group. This application will be made available from the address https://space.example.com/meteor.
The company needs a solution that can automatically scale from a small number of requests overnight to a large number of requests for a future meteor shower.
What is the MOST operationally efficient solution that meets these requirements?
A. Create a Network Load Balancer (NLB). Configure the NLB to listen on two ports. Configure a target group for one port to deliver all IP traffic to the Auto Scaling group to process the custom images.
Configure a target group for the second port to deliver all IP traffic to Fargate Use path-based routing in the ALB to route traffic for the URL prefix /meteor to the first target group. Route all other paths to the second target group.
B. Place the ALB behind an Amazon CloudFront distribution. Create a Lambda@Edge function that parses the request URI and adds the path-pattern header with the IP addresses of the EC2 instances to any request for /meteor. Add a listener rule to the ALB that looks for the HTTP header and uses the IP addresses of the EC2 instances to forward the traffic.
C. Update the existing target group with the new EC2 instances. Update the application's ALB by adding a listener rule that redirects /meteor to the newly added EC2 instances.
D. Create a new target group. Configure the Auto Scaling group of the EC2 instances to use the target group Update the ALB by adding a listener rule that redirects /meteor to the new target group.
Answer: C
