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The Microsoft Certified: Azure AI Fundamentals qualification authenticates the learner's understanding and skills in AI & ML concepts along with associated Azure services. In particular, the individual with this certification is competent in demonstrating their understanding of various workloads related to those terms along with their implementation in Azure cloud computing services. In addition, this certification is an excellent way to get a step ahead in the preparation for other role-based Azure certificates as well as showcasing one's skill in the fundamentals of ML as well as AI. All in all, the Azure AI Fundamentals validation form Microsoft is for beginners and thus, doesn't require any technical knowledge and expertise like, for example, engineering for software. However, some understanding of programming will help you a lot to easily nail test AI-900.
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This certification test is available in English, Spanish, Simplified Chinese, Japanese, French, Korean, and German. You will find different formats of questions while dealing with this Microsoft exam. These include multiple choice, drag and drop, build list, active screen, short answer, and best answer. The test costs $99 and the learners can register for it through Pearson VUE or Certiport.
The AI-900 exam covers various topics, including the fundamentals of AI, Azure AI services, computer vision, natural language processing, and conversational AI. AI-900 Exam is designed to test your ability to work with Azure AI services, such as Azure Cognitive Services and Azure Machine Learning. You will also need to demonstrate your knowledge of key Azure tools that support AI and ML workloads, such as Azure Notebooks and Azure Databricks.
NEW QUESTION # 195
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
Graphical user interface, text, application, email Description automatically generated
NEW QUESTION # 196
You send an image to a Computer Vision API and receive back the annotated image shown in the exhibit.
Which type of computer vision was used?
Answer: D
Explanation:
Explanation
Object detection is similar to tagging, but the API returns the bounding box coordinates (in pixels) for each object found. For example, if an image contains a dog, cat and person, the Detect operation will list those objects together with their coordinates in the image. You can use this functionality to process the relationships between the objects in an image. It also lets you determine whether there are multiple instances of the same tag in an image.
The Detect API applies tags based on the objects or living things identified in the image. There is currently no formal relationship between the tagging taxonomy and the object detection taxonomy. At a conceptual level, the Detect API only finds objects and living things, while the Tag API can also include contextual terms like
"indoor", which can't be localized with bounding boxes.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-detection
NEW QUESTION # 197
Select the answer that correctly completes the sentence.
Answer:
Explanation:
Explanation
NEW QUESTION # 198
Which natural language processing feature can be used to identify the main talking points in customer feedback surveys?
Answer: C
NEW QUESTION # 199
To complete the sentence, select the appropriate option in the answer area.
Answer:
Explanation:
NEW QUESTION # 200
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