Free PDF Microsoft - AI-900 - Fantastic Test Microsoft Azure AI Fundamentals Valid

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The AI-900 Exam covers a wide range of topics related to AI and ML such as Understanding AI workloads and considerations, Understanding fundamental principles of machine learning on Azure, Understanding features of computer vision workloads on Azure, Understanding features of Natural Language Processing (NLP) workloads on Azure, Understanding features of conversational AI workloads on Azure, and many more.

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Describe the Basic Principles of ML on Microsoft Azure (30-35%)

As for this area, it includes the following:

Explain the abilities of the No-code ML with Azure ML Learning Studio – This domain equips the individuals with the knowledge of the Azure ML designer and automated ML UI.
Identify the major tasks in crafting an ML solution – This subject area measures the students’ competence in explaining some concepts, such as basic features of data preparation and ingestion, model management and deployment, model training & evaluation, and feature selection and engineering.
Describe the ML core concepts – You should be able to identify the labels and features within a dataset for ML and describe the usage of validation datasets and training in ML. The applicants also need the ability to explain the usage of ML algorithms in model training, as well as interpret and choose the model evaluation yardsticks for regression and classification.
Identify the basic ML types – This section equips the learners with the ability to identify various concepts, such as regression, clustering, and classification ML scenarios.

Microsoft Azure AI Fundamentals Sample Questions (Q53-Q58):

NEW QUESTION # 53
Match the types of machine learning to the appropriate scenarios.
To answer, drag the appropriate machine learning type from the column on the left to its scenario on the right. Each machine learning type may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION # 54
Match the Microsoft guiding principles for responsible AI to the appropriate descriptions.
To answer, drag the appropriate principle from the column on the left to its description on the right. Each principle may be used once, more than once, or not at all.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

NEW QUESTION # 55
You need to make the press releases of your company available in a range of languages.
Which service should you use?

A. Speech
B. Translator Text
C. Language Understanding (LUIS)
D. Text Analytics

Answer: B

Explanation:
Press release is a written communication. Speech wouldn't make sense. Plus, the Speech service doesn't translate languages, it "translates" audio into text, and vice versa.
https://docs.microsoft.com/en-us/learn/modules/translate-text-with-translation-service/2-get-started-azure

NEW QUESTION # 56
Select the answer that correctly completes the sentence.

Answer:

Explanation:
Explanation

NEW QUESTION # 57
You are developing a chatbot solution in Azure.
Which service should you use to determine a user's intent?

A. Speech
B. Language Understanding (LUIS)
C. Translator Text
D. QnA Maker

Answer: B

Explanation:
Language Understanding (LUIS) is a cloud-based API service that applies custom machine-learning intelligence to a user's conversational, natural language text to predict overall meaning, and pull out relevant, detailed information.
Design your LUIS model with categories of user intentions called intents. Each intent needs examples of user utterances. Each utterance can provide data that needs to be extracted with machine-learning entities.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/luis/what-is-luis

NEW QUESTION # 58
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