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Eliminates confusion while taking the Microsoft AI-102 certification exam. Prepares you for the format of your Microsoft AI-102 exam dumps, including multiple-choice questions and fill-in-the-blank answers. Comprehensive, up-to-date coverage of the entire Microsoft AI-102 Certification curriculum.

Microsoft AI-102 certification exam is an essential certification for professionals who want to demonstrate their expertise in developing and implementing AI solutions in the Azure environment. By passing AI-102 exam, you will be able to showcase your skills and knowledge to potential employers and enhance your career prospects in the field of AI.

In addition to technical skills, the Microsoft AI-102 exam also tests candidates' ability to design AI solutions that meet business requirements. This includes understanding how to assess the feasibility of different AI solutions, identify relevant use cases, and evaluate the impact of AI on business processes. Candidates will also be tested on their ability to communicate the benefits and limitations of AI to stakeholders.

The benefit of obtaining the AI-102: Designing and Implementing an Azure AI Solution Exam Certification

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Microsoft Designing and Implementing a Microsoft Azure AI Solution Sample Questions (Q115-Q120):

NEW QUESTION # 115
You are building an app that will scan confidential documents and use the Language service to analyze the contents.
You provision an Azure Cognitive Services resource.
You need to ensure that the app can make requests to the Language service endpoint. The solution must ensure that confidential documents remain on-premises.
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.

Answer:

Explanation:

Explanation:


NEW QUESTION # 116
You have a factory that produces cardboard packaging for food products. The factory has intermittent internet connectivity.
The packages are required to include four samples of each product.
You need to build a Custom Vision model that will identify defects in packaging and provide the location of the defects to an operator. The model must ensure that each package contains the four products.
Which project type and domain should you use? To answer, drag the appropriate options to the correct targets.
Each option 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:

Explanation:

Explanation:
Project type: Object detection
Domain: General (compact)
The scenario requires building a Custom Vision model for a factory with intermittent internet connectivity.
The solution must:
Detect defects in packaging
Locate the defects (provide bounding box information)
Ensure each package contains four products
Support offline use due to intermittent connectivity
Step 1 - Determine Project Type
Image Classification: Assigns a label to an image, but cannot locate where objects/defects are in the image.
Object Detection: Identifies what objects are present and their location (via bounding boxes).
Since the requirement is to identify location of defects and count products, the correct choice is Object detection.
Step 2 - Determine Domain
General domain: Standard general-purpose domain, optimized for cloud inference.
General (compact) domain: A lightweight version designed for exporting models to run offline on edge devices (iOS, Android, ONNX, etc.). Perfect for scenarios with intermittent internet connectivity.
Food domain: Specialized for food image classification, not defect detection in packaging.
Logo domain: Specialized for logo recognition, irrelevant here.
Since the requirement includes offline capability, the correct domain is General (compact).
Project type: Object detection
Domain: General (compact)
Microsoft References
Custom Vision project types: Classification vs Object detection
Domains in Custom Vision (General, General compact, Food, Logo, etc.)
Exporting compact models for offline use


NEW QUESTION # 117
You are developing an application to recognize employees' faces by using the Face Recognition API. Images of the faces will be accessible from a URI endpoint.
The application has the following code.

For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE:Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
A. True
B. True
C. True
B: see this example code from documentation that uses PersonGroup of size 10,000 :
https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/how-to-add-faces the question wants to trick you into thinking you need to use a LargePersonGroup for a size of 10,000 - but the documentation for it doesn't include this limitation or criteria:https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/how-to-use-large-s Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/face/face-api-how-to-topics/use-persondirectory


NEW QUESTION # 118
You train a Custom Vision model used in a mobile app.
You receive 1,000 new images that do not have any associated data.
You need to use the images to retrain the model. The solution must minimize how long it takes to retrain the model.
Which three actions should you perform in the Custom Vision portal? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

Answer:

Explanation:

Explanation:
Comprehensive Detailed ExplanationYou have 1,000 untagged images and want to retrain the Custom Vision model as quickly as possible. The key is to avoid manually tagging every image, since that is time-consuming.
Step 1: Upload all the images
* First, bulk upload all the untagged images into the Custom Vision project.
* At this stage, they will have no labels.
Step 2: Get suggested tags
* The Custom Vision portal offers an auto-suggest feature that uses the current trained model to predict tags for new, untagged images.
* This dramatically reduces manual tagging effort.
Step 3: Review the suggestions and confirm the tags
* Auto-suggestions are not always 100% accurate, so you must confirm or correct them.
* Once confirmed, the dataset is labeled properly and ready for retraining.
Why not the other options?
* Upload the images by category / group into category folders: This is only helpful if the images already have known categories, but here they arrive untagged.
* Tag the images manually: This would take much longer and contradicts the requirement to minimize time.
* Upload all the images.
* Get suggested tags.
* Review the suggestions and confirm the tags.
Correct Sequence
* Custom Vision - Tag images
* Custom Vision - Suggested tags with predictions
Microsoft References


NEW QUESTION # 119
You are reviewing the design of a chatbot. The chatbot includes a language generation file that contains the following fragment.
# Greet(user)
- ${Greeting()}, ${user.name}
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://docs.microsoft.com/en-us/composer/how-to-ask-for-user-input


NEW QUESTION # 120
......

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