During the process of Machine Learning, when should you review evaluation metrics?
Answer(s): D
You have a natural language processing (NLP) model that was created by using data obtained without permission.Which Microsoft principle for responsible AI does this breach?
Answer(s): B
DRAG DROP (Drag and Drop is not supported)Match the services to the appropriate descriptions.To answer, drag the appropriate service from the column on the left to its description on the right. Each service may be used once, more than once, or not at all.Note: Each correct match is worth one point.Select and Place:
Answer(s): A
Box 1: Azure Bot ServiceYou can link a Language Service knowledge base to an Azure Bot Service.Box 2: SpeechLanguage and voice support for the Speech service.Speech service provides speech-to-text, text-to-speech, pronunciation assessment, speech translation, speaker recognition, and additional service features.Incorrect:* Language Service
https://learn.microsoft.com/en-us/azure/cognitive-services/qnamaker/tutorials/create-faq-bot-with- azure-bot-service https://learn.microsoft.com/en-us/azure/cognitive-services/speech-service/language-support https://learn.microsoft.com/en-us/azure/architecture/solution-ideas/articles/loan-chargeoff-prediction-with-sql- server
Which machine learning technique can be used for anomaly detection?
Anomaly Detector, an AI service that helps you foresee problems before they occur.Easily embed time-series anomaly detection capabilities into your apps to help users identify problems quickly.Anomaly Detector ingests time-series data of all types and selects the best anomaly detection algorithm for your data to ensure high accuracy. Detect spikes, dips, deviations from cyclic patterns, and trend changes through both univariate and multivariate APIs. Customize the service to detect any level of anomaly. Deploy the anomaly detection service where you need it -- in the cloud or at the intelligent edge.
https://azure.microsoft.com/en-us/products/cognitive-services/anomaly-detector
You have an AI-based loan approval system.During testing, you discover that the system has a gender bias.Which responsible AI principle does this violate?
Fairness - AI systems should treat all people fairlyIncorrect:Accountability - People should be accountable for AI systems Reliability & Safety - AI systems should perform reliably and safely Transparency - AI systems should be understandable
https://dataninja.medium.com/6-principles-of-responsible-ai-b90f745b73dc
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