2025 100% FREE AI-900–THE BEST 100% FREE RELIABLE EXAM LABS | EXAM MICROSOFT AZURE AI FUNDAMENTALS GUIDE

2025 100% Free AI-900–The Best 100% Free Reliable Exam Labs | Exam Microsoft Azure AI Fundamentals Guide

2025 100% Free AI-900–The Best 100% Free Reliable Exam Labs | Exam Microsoft Azure AI Fundamentals Guide

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Tags: AI-900 Reliable Exam Labs, Exam AI-900 Guide, AI-900 Exam Actual Tests, AI-900 Exam Sample Questions, Valid AI-900 Exam Dumps

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Exam Microsoft AI-900 Guide & AI-900 Exam Actual Tests

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The Microsoft AI-900 Exam consists of multiple-choice questions, and individuals have to score a minimum of 700 points out of 1000 to pass the exam. AI-900 exam can be taken online, and individuals can prepare for the exam by taking online courses or attending training sessions. Microsoft offers various training resources, including online courses, practice tests, and instructor-led training, to help individuals prepare for the exam.

Microsoft Azure AI Fundamentals Sample Questions (Q92-Q97):

NEW QUESTION # 92
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. Enable Explain best model.
  • B. Set Validation type to Auto.
  • C. Set Primary metric to accuracy.
  • D. Set Max concurrent iterations to 0.

Answer: A

Explanation:
Model Explain Ability.
Most businesses run on trust and being able to open the ML "black box" helps build transparency and trust. In heavily regulated industries like healthcare and banking, it is critical to comply with regulations and best practices. One key aspect of this is understanding the relationship between input variables (features) and model output. Knowing both the magnitude and direction of the impact each feature (feature importance) has on the predicted value helps better understand and explain the model. With model explain ability, we enable you to understand feature importance as part of automated ML runs.
Reference:
https://azure.microsoft.com/en-us/blog/new-automated-machine-learning-capabilities-in-azure-machine-learning-service/


NEW QUESTION # 93
Select the answer that correctly completes the sentence.

Answer:

Explanation:

Explanation:


NEW QUESTION # 94
You need to predict the sea level in meters for the next 10 years.
Which type of machine learning should you use?

  • A. classification
  • B. clustering
  • C. regression

Answer: C

Explanation:
Explanation
In the most basic sense, regression refers to prediction of a numeric target.
Linear regression attempts to establish a linear relationship between one or more independent variables and a numeric outcome, or dependent variable.
You use this module to define a linear regression method, and then train a model using a labeled dataset. The trained model can then be used to make predictions.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regression Regression is a form of machine learning that is used to predict a based on an item's features.
https://docs.microsoft.com/en-us/learn/modules/create-regression-model-azure-machine-learning-designer/introd


NEW QUESTION # 95
You are developing a model to predict events by using classification.
You have a confusion matrix for the model scored on test data as shown in the following exhibit.

Use the drop-down menus to select the answer choice that completes each statement based on the information presented in the graphic.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:


Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance Finding TP is easy. It basically means the value where Predicted and True value is 1 and that is 11 in this case.
False Negative means where true value was 1 but predicted value was 0 and that is 1033 in this case The confusion matrix shows cases where both the predicted and actual values were 1 (known as true positives) at the top left, and cases where both the predicted and the actual values were 0 (true negatives) at the bottom right. The other cells show cases where the predicted and actual values differ (false positives and false negatives).
https://docs.microsoft.com/en-us/learn/modules/create-classification-model-azure-machine-learning-designer/evaluate-model


NEW QUESTION # 96
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:
Explanation

Reference:
https://azure.microsoft.com/en-gb/services/cognitive-services/speech-to-text/#features Speech recognition means Speech to Text. In the above example as a person speaks the words are converted into text of the same language. Hence Speech to Text also called Speech recognition is the right answer.
Speech recognition - the ability to detect and interpret spoken input.
Speech synthesis - the ability to generate spoken output.
https://docs.microsoft.com/en-us/learn/modules/recognize-synthesize-speech/1-introduction


NEW QUESTION # 97
......

Students are given a fixed amount of time to complete each test, thus Microsoft Exam Questions candidate's ability to control their time and finish the Microsoft AI-900 exam in the allocated time is a crucial qualification. Obviously, this calls for lots of practice. Taking PassTestking AI-900 Practice Exam helps you get familiar with the Microsoft Azure AI Fundamentals (AI-900) exam questions and work on your time management skills in preparation for the real Microsoft Azure AI Fundamentals (AI-900) exam.

Exam AI-900 Guide: https://www.passtestking.com/Microsoft/AI-900-practice-exam-dumps.html

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