New AI-900 Exam Questions To Pass Microsoft Azure AI Fundamentals

New AI-900 Exam Questions are available at PassQuestion, you will practice all AI-900 questions and answers to help you familiar with the questions pattern and objectives tested in the Microsoft Azure AI Fundamentals exam, you are guaranteed to pass your Microsoft AI-900 exam successfully in your first time.

New AI-900 Exam Questions To Pass Microsoft Azure AI Fundamentals

1. A company employs a team of customer service agents to provide telephone and email support to customers. The company develops a webchat bot to provide automated answers to common customer queries.

Which business benefit should the company expect as a result of creating the webchat bot solution?


2. For a machine learning progress, how should you split data for training and evaluation?


3. You build a machine learning model by using the automated machine learning user interface (UI).

You need to ensure that the model meets the Microsoft transparency principle for responsible AI.

What should you do?


4. You are designing an AI system that empowers everyone, including people who have hearing, visual, and other impairments.

This is an example of which Microsoft guiding principle for responsible AI?


5. Which service should you use to extract text, key/value pairs, and table data automatically from scanned documents?


6. You use Azure Machine Learning designer to publish an inference pipeline.

Which two parameters should you use to consume the pipeline? Each correct answer presents part of the solution. NOTE: Each correct selection is worth one point.


7. Which metric can you use to evaluate a classification model?


8. Which two components can you drag onto a canvas in Azure Machine Learning designer? Each correct answer presents a complete solution. NOTE: Each correct selection is worth one point.


9. You need to create a training dataset and validation dataset from an existing dataset.

Which module in the Azure Machine Learning designer should you use?


10. Which type of machine learning should you use to predict the number of gift cards that will be sold next month?


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