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| Section | Weight | Objectives |
|---|---|---|
| Topic 1: Fundamental principles of machine learning on Azure | 15–20% | - Describe core concepts of machine learning - Describe machine learning pipelines - Describe capabilities of Azure Machine Learning - Describe automated machine learning |
| Topic 2: Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Describe capabilities of Azure Speech - Describe capabilities of Azure Language - Identify types of NLP solutions - Describe capabilities of Azure Translator |
| Topic 3: Artificial Intelligence workloads and considerations | 15–20% | - Identify types of AI workloads - Describe considerations for developing AI solutions - Describe responsible AI principles |
| Topic 4: Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Form Recognizer - Describe capabilities of Azure Custom Vision - Identify types of computer vision solutions - Describe capabilities of Azure Face - Describe capabilities of Azure Computer Vision |
| Topic 5: Features of generative AI workloads on Azure | 20–25% | - Describe use cases for generative AI - Describe responsible AI practices for generative AI - Describe capabilities of Azure OpenAI Service - Describe generative AI concepts |
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NEW QUESTION # 321
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/azure/machine-learning/concept-designer
NEW QUESTION # 322
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cloud-adoption-framework/innovate/best-practices/trusted-ai
NEW QUESTION # 323
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
.
Reference:
https://docs.microsoft.com/en-us/dotnet/machine-learning/resources/tasks
NEW QUESTION # 324
Which two languages can you use to write custom code for Azure Machine Learning designer? Each correct answer presents a complete solution.
NOTE; Each correct selection is worth one point.
Answer: A,D
Explanation:
According to the Microsoft Learn module "Describe features of Azure Machine Learning" and the AI-900 study guide, Azure Machine Learning designer supports extending workflows through custom code modules written in Python and R.
* Python is the most commonly used language for AI and machine learning due to its extensive library support (such as TensorFlow, Scikit-learn, and PyTorch).
* R is widely used for statistical computing and data visualization, making it valuable for analytical workloads.
In Azure Machine Learning, users can insert Python Script or Execute R Script modules within the visual designer to perform advanced operations or custom data transformations.
C# and Scala are not supported directly in Azure Machine Learning Designer. C# is more common in application development, and Scala is primarily used in big data frameworks like Apache Spark.
Hence, the correct answers are C. Python and D. R.
NEW QUESTION # 325
You are building a tool that will process images from retail stores and identify the products of competitors.
The solution will use a custom model.
Which Azure Cognitive Services service should you use?
Answer: B
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/overview
NEW QUESTION # 326
......
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