Download Microsoft Azure AI Fundamentals.VCEplus.AI-900.2020-09-08.1e.36q.vcex

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Exam Microsoft Azure AI Fundamentals
Number AI-900
File Name Microsoft Azure AI Fundamentals.VCEplus.AI-900.2020-09-08.1e.36q.vcex
Size 1.06 Mb
Posted September 08, 2020
Downloads 238

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Demo Questions

Question 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?

  • A: increased sales
  • B: a reduced workload for the customer service agents
  • C: improved product reliability

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

  • A: Use features for training and labels for evaluation.
  • B: Randomly split the data into rows for training and rows for evaluation.
  • C: Use labels for training and features for evaluation.
  • D: Randomly split the data into columns for training and columns for evaluation.

Question 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?

  • A: Set Validation type to Auto.
  • B: Enable Explain best model.
  • C: Set Primary metric to accuracy.
  • D: Set Max concurrent iterations to 0.

Question 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?

  • A: fairness
  • B: inclusiveness
  • C: reliability and safety
  • D: accountability

Question 5
To complete the sentence, select the appropriate option in the answer area.

Question 6
Which service should you use to extract text, key/value pairs, and table data automatically from scanned documents?

  • A: Form Recognizer
  • B: Text Analytics
  • C: Ink Recognizer
  • D: Custom Vision

Question 7
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.

  • A: the model name
  • B: the training endpoint
  • C: the authentication key
  • D: the REST endpoint

Question 8
Which metric can you use to evaluate a classification model?

  • A: true positive rate
  • B: mean absolute error (MAE)
  • C: coefficient of determination (R2)
  • D: root mean squared error (RMSE)

Question 9
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.

  • A: dataset
  • B: compute
  • C: pipeline
  • D: module

Question 10
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?

  • A: Select Columns in Dataset
  • B: Add Rows
  • C: Split Data
  • D: Join Data


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