Exam AI-900 topic 1 question 12 discussion

Actual exam question from Microsoft's AI-900

Question #: 12
Topic #: 1

DRAG DROP -
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.
Select and Place:

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Suggested Answer:

Reference:
https://docs.microsoft.com/en-us/learn/paths/get-started-with-artificial-intelligence-on-azure/

by Derin_tade at May 31, 2021, 9:59 a.m.

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idioteque

Highly Voted 2 months, 2 weeks ago

For me to remember haha xD Computer vision = identify (object) letters NLP = sentiment Anomaly Detection = fraud Maching Learning (regression) = predict

upvoted 26 times

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zellck

Highly Voted 2 months, 2 weeks ago

1. Computer vision 2. Natural language processing 3. Anomaly detection 4. ML (Regression) https://learn.microsoft.com/en-us/azure/cognitive-services/computer-vision/overview-ocr OCR or Optical Character Recognition is also referred to as text recognition or text extraction. Machine-learning based OCR techniques allow you to extract printed or handwritten text from images, such as posters, street signs and product labels, as well as from documents like articles, reports, forms, and invoices. The text is typically extracted as words, text lines, and paragraphs or text blocks, enabling access to digital version of the scanned text. This eliminates or significantly reduces the need for manual data entry.

upvoted 6 times

zellck

1 year, 5 months ago

https://learn.microsoft.com/en-us/training/modules/create-regression-model-azure-machine-learning-designer/2-regression-scenarios Regression is a form of machine learning used to understand the relationships between variables to predict a desired outcome. Regression predicts a numeric label or outcome based on variables, or features. For example, an automobile sales company might use the characteristics of a car (such as engine size, number of seats, mileage, and so on) to predict its likely selling price. In this case, the characteristics of the car are the features, and the selling price is the label.

upvoted 3 times

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zellck

1 year, 5 months ago

https://learn.microsoft.com/en-us/azure/cognitive-services/language-service/sentiment-opinion-mining/overview Sentiment analysis and opinion mining are features offered by Azure Cognitive Service for Language, a collection of machine learning and AI algorithms in the cloud for developing intelligent applications that involve written language. These features help you find out what people think of your brand or topic by mining text for clues about positive or negative sentiment, and can associate them with specific aspects of the text. https://learn.microsoft.com/en-us/azure/cognitive-services/anomaly-detector/overview Anomaly Detector is an AI service with a set of APIs, which enables you to monitor and detect anomalies in your time series data with little machine learning (ML) knowledge, either batch validation or real-time inference.

upvoted 3 times

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kim21

Most Recent 1 month, 3 weeks ago

Computer vision: This involves teaching machines to interpret and understand visual information, such as identifying handwritten letters or detecting objects in images. Natural language processing (NLP): This field of AI deals with analyzing and understanding human language. It can be used to predict the sentiment of social media posts, translate languages, or respond to voice commands. Anomaly detection: This method identifies data points or events that deviate from the norm, such as detecting fraudulent credit card payments. Machine Learning (Regression): This involves predicting continuous outcomes, such as predicting next month's sales based on historical data.

upvoted 3 times

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