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Microsoft AI-900 exam is an associate level certification which is a three to five-hour exam that covers the technologies necessary for building intelligent applications for cloud computing. Students should have a solid knowledge of Microsoft Azure IaaS, services, APIs, SQL Server 2017. Role of Azure Intelligent Solutions. Windows 2012, Windows 2016, and SQL Server 2017. .NET Framework 4.6.1 (or 4.7), or higher. Resident Deployment of the Solutions.Classify application workloads. Apply Azure monitoring and analytics, Operations Management Suite (OMS) logs, and Event Hubs. Manage the master database. Implement master database failover. Microsoft AI-900 exam dumps aligns with the objectives listed below.Classify application workloads. Deploy, configure, set up, activate, maintain, troubleshoot and support all necessary Azure services. Manage the master database.
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NEW QUESTION # 224
You have an app that identifies birds in images. The app performs the following tasks:
* Identifies the location of the birds in the image
* Identifies the species of the birds in the image
Which type of computer vision does each task use? To answer, select the appropriate options in the answer area.
NOTE: Each correct selection is worth one point.
Answer:
Explanation:
NEW QUESTION # 225
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:
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/anomaly-detection
NEW QUESTION # 226
You need to predict the income range of a given customer by using the following dataset.
Which two fields should you use as features? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
Answer: A,E
Explanation:
Explanation
First Name, Last Name, Age and Education Level are features. Income range is a label (what you want to predict). First Name and Last Name are irrelevant in that they have no bearing on income. Age and Education level are the features you should use.
NEW QUESTION # 227
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:
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/Translator/translator-info-overview
https://docs.microsoft.com/en-us/legal/cognitive-services/speech-service/speech-to-text/transparency-note
NEW QUESTION # 228
Which Azure Machine Learning capability should you use to quickly build and deploy a predictive model without extensive coding?
Answer: D
Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) curriculum and Microsoft Learn's "Explore Automated Machine Learning in Azure Machine Learning" module, Automated ML (AutoML) is the Azure Machine Learning capability that allows users to quickly build, train, and deploy predictive models with minimal or no coding experience.
Automated ML automatically performs tasks that would normally require expert data science knowledge, such as:
* Selecting appropriate algorithms (e.g., decision trees, logistic regression, random forests)
* Performing hyperparameter tuning to optimize model accuracy
* Handling missing data and feature scaling automatically
* Generating performance metrics and best model recommendations
This feature is especially useful for business analysts, developers, or beginners who want to leverage machine learning for predictions (like sales forecasting, churn analysis, or demand prediction) without having to write complex Python code.
Other options explained:
* A. ML pipelines automate and organize workflows for model training and deployment but still require pre-built models.
* B. Copilot is an AI-powered assistant embedded in Microsoft tools for productivity, not a model training feature.
* C. DALL-E is an image generation model under Azure OpenAI, not a predictive modeling tool.
Thus, per official Microsoft Learn content, Automated Machine Learning is the correct capability to quickly build and deploy predictive models with minimal coding.
NEW QUESTION # 229
......
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