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| Section | Weight | Objectives |
|---|---|---|
| Fundamental principles of machine learning on Azure | 15–20% | - Describe core concepts of machine learning - Describe automated machine learning - Describe machine learning pipelines - Describe capabilities of Azure Machine Learning |
| Features of computer vision workloads on Azure | 15–20% | - Describe capabilities of Azure Computer Vision - Identify types of computer vision solutions - Describe capabilities of Azure Face - Describe capabilities of Azure Form Recognizer - Describe capabilities of Azure Custom Vision |
| Artificial Intelligence workloads and considerations | 15–20% | - Describe responsible AI principles - Identify types of AI workloads - Describe considerations for developing AI solutions |
| Features of generative AI workloads on Azure | 20–25% | - Describe responsible AI practices for generative AI - Describe generative AI concepts - Describe capabilities of Azure OpenAI Service - Describe use cases for generative AI |
| Features of Natural Language Processing (NLP) workloads on Azure | 15–20% | - Describe capabilities of Azure Language - Describe capabilities of Azure Speech - Describe capabilities of Azure Translator - Identify types of NLP solutions |
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NEW QUESTION # 212
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: B,C
NEW QUESTION # 213
Match the facial recognition tasks to the appropriate questions.
To answer, drag the appropriate task from the column on the left to its question on the right. Each task may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/face/#features
NEW QUESTION # 214
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:
NEW QUESTION # 215
Select the answer that correctly completes the sentence.
Answer:
Explanation:
NEW QUESTION # 216
In Azure Machine Learning, what are two ensemble methods for combining models in automated machine learning (automated ML)? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Answer: B,D
NEW QUESTION # 217
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