[Jan 18, 2024] Fully Updated Dumps PDF – Latest AI-900 Exam Questions and Answers [Q17-Q31]

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[Jan 18, 2024] Fully Updated Dumps PDF – Latest AI-900 Exam Questions and Answers

100% Free AI-900 Exam Dumps to Pass Exam Easily from Free4Dump

Microsoft AI-900 certification exam covers a wide range of topics related to AI and machine learning, including fundamental concepts such as machine learning models, data analysis, and natural language processing. AI-900 exam also covers more advanced topics such as computer vision, speech recognition, and intelligent decision-making. Microsoft Azure AI Fundamentals certification exam is designed to test an individual’s knowledge of AI concepts and their ability to apply them to real-world scenarios using Microsoft Azure services.

NEW QUESTION 17
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Reference:
https://docs.microsoft.com/en-us/azure/bot-service/bot-service-overview-introduction?view=azure-bot-service-4.0

NEW QUESTION 18
Match the machine learning tasks to the appropriate scenarios.
To answer, drag the appropriate task from the column on the left to its scenario on the right. Each task may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

Explanation:
Box 1: Model evaluation
The Model evaluation module outputs a confusion matrix showing the number of true positives, false negatives, false positives, and true negatives, as well as ROC, Precision/Recall, and Lift curves.
Box 2: Feature engineering
Feature engineering is the process of using domain knowledge of the data to create features that help ML algorithms learn better. In Azure Machine Learning, scaling and normalization techniques are applied to facilitate feature engineering. Collectively, these techniques and feature engineering are referred to as featurization.
Note: Often, features are created from raw data through a process of feature engineering. For example, a time stamp in itself might not be useful for modeling until the information is transformed into units of days, months, or categories that are relevant to the problem, such as holiday versus working day.
Box 3: Feature selection
In machine learning and statistics, feature selection is the process of selecting a subset of relevant, useful features to use in building an analytical model. Feature selection helps narrow the field of data to the most valuable inputs. Narrowing the field of data helps reduce noise and improve training performance.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio/evaluate-model-performance
https://docs.microsoft.com/en-us/azure/machine-learning/concept-automated-ml

NEW QUESTION 19
Which metric can you use to evaluate a classification model?

true positive rate

mean absolute error (MAE)

coefficient of determination (R2)

root mean squared error (RMSE)

Section: Describe fundamental principles of machine learning on Azure
Explanation:
What does a good model look like?
An ROC curve that approaches the top left corner with 100% true positive rate and 0% false positive rate will be the best model. A random model would display as a flat line from the bottom left to the top right corner.
Worse than random would dip below the y=x line.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/how-to-understand-automated-ml#classification

NEW QUESTION 20
Select the answer that correctly completes the sentence.

NEW QUESTION 21
To complete the sentence, select the appropriate option in the answer area.

Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/getting-started-build-a-classifier

NEW QUESTION 22
To complete the sentence, select the appropriate option in the answer area.

Explanation
Text Description automatically generated

Regression is a machine learning task that is used to predict the value of the label from a set of related features.
Reference:
https://docs.microsoft.com/en-us/dotnet/machine-learning/resources/tasks

NEW QUESTION 23
You need to identify street names based on street signs in photographs.
Which type of computer vision should you use?

object detection

optical character recognition (OCR)

image classification

facial recognition

NEW QUESTION 24
Select the .

NEW QUESTION 25
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Reference:
https://machinelearningmastery.com/difference-test-validation-datasets/

NEW QUESTION 26
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/anomaly-detection

NEW QUESTION 27
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Explanation:
The Text Analytics API is a cloud-based service that provides advanced natural language processing over raw text, and includes four main functions: sentiment analysis, key phrase extraction, named entity recognition, and language detection.
Box 1: Yes
You can detect which language the input text is written in and report a single language code for every document submitted on the request in a wide range of languages, variants, dialects, and some regional/cultural languages. The language code is paired with a score indicating the strength of the score.
Box 2: No
Box 3: Yes
Named Entity Recognition: Identify and categorize entities in your text as people, places, organizations, date/time, quantities, percentages, currencies, and more. Well-known entities are also recognized and linked to more information on the web.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/text-analytics/overview

NEW QUESTION 28
You have a website that includes customer reviews.
You need to store the reviews in English and present the reviews to users in their respective language by recognizing each users geographical location.
Which type of natural language processing workload should you use?

translation

language modeling

key phrase extraction

speech recognition

NEW QUESTION 29
For each of the following statements, select Yes if the statement is True. Otherwise, select No. NOTE: Each correct selection is worth one point.

NEW QUESTION 30
To complete the sentence, select the appropriate option in the answer area.

NEW QUESTION 31
You plan to deploy an Azure Machine Learning model by using the Machine Learning designer Which four actions should you perform in sequence? To answer, move the appropriate actions from the list of actions to the answer area and arrange them in the correct order.

1 – Ingest and prepare a dataset.
2 – Split the data randomly into training data and validation data
3 – Train the model.
4 – Evaluation the model against the validation dataset.

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