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NEW QUESTION 28
Match the types of AI workloads to the appropriate scenarios.
To answer, drag the appropriate workload type from the column on the left to its scenario on the right. Each workload type may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Reference:
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language- processing
NEW QUESTION 29
Match the types of machine learning to the appropriate scenarios.
To answer, drag the appropriate machine learning type from the column on the left to its scenario on the right. Each machine learning type may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
Explanation:
Box 1: Regression
In the most basic sense, regression refers to prediction of a numeric target.
Linear regression attempts to establish a linear relationship between one or more independent variables and a numeric outcome, or dependent variable.
You use this module to define a linear regression method, and then train a model using a labeled dataset. The trained model can then be used to make predictions.
Box 2: Classification
Classification is a machine learning method that uses data to determine the category, type, or class of an item or row of data.
Box 3: Clustering
Clustering, in machine learning, is a method of grouping data points into similar clusters. It is also called segmentation.
Over the years, many clustering algorithms have been developed. Almost all clustering algorithms use the features of individual items to find similar items. For example, you might apply clustering to find similar people by demographics. You might use clustering with text analysis to group sentences with similar topics or sentiment.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regression
NEW QUESTION 30
You need to make the press releases of your company available in a range of languages.
Which service should you use?
- A. Text Analytics
- B. Speech
- C. Language Understanding (LUIS)
- D. Translator Text
Answer: D
Explanation:
Press release is a written communication. Speech wouldn't make sense. Plus, the Speech service doesn't translate languages, it “translates” audio into text, and vice versa.
https://docs.microsoft.com/en-us/learn/modules/translate-text-with-translation-service/2-get-started-azure
NEW QUESTION 31
Which AI service can you use to interpret the meaning of a user input such as “Call me back later?”
- A. Text Analytics
- B. Translator Text
- C. Speech
- D. Language Understanding (LUIS)
Answer: A
Explanation:
Section: Describe features of Natural Language Processing (NLP) workloads on Azure Explanation:
Text Analytics is an AI service that uncovers insights such as sentiment, entities, and key phrases in unstructured text.
Incorrect Answers:
D: Language Understanding (LUIS) is a cloud-based API service, not an AI service, that applies custom machine-learning intelligence to a user's conversational, natural language text to predict overall meaning, and pull out relevant, detailed information.
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/text-analytics/
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/what-is-luis
NEW QUESTION 32
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?
- A. optical character recognition (OCR)
- B. object detection
- C. semantic segmentation
- D. image classification
Answer: B
Explanation:
Section: Describe features of computer vision workloads on Azure
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 33
……
