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It is important to cover Microsoft Azure AI Fundamentals (AI-900) exam topics and check if you need to practice them. If you are talking about the Microsoft AI-900 certification exam, you need to practice and overcome mistakes. If you do not practice for it, chances are that you might get confused while appearing for the AI-900 Exam. When you get the test study material, it comes with the Microsoft AI-900 practice exams (desktop & web-based) to solve.

The AI-900 exam is suitable for individuals who are looking to develop their skills and knowledge in AI and machine learning, regardless of their background or experience level. AI-900 exam is also ideal for students who are interested in pursuing a career in AI and want to gain a fundamental understanding of the technology. For professionals, the AI-900 Exam can help you demonstrate your knowledge and expertise in AI, which can lead to better job opportunities and higher salaries.

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A second format is a Microsoft AI-900 web-based practice exam that can take for self-assessment. However, it differs from desktop-based AI-900 practice exam software as it can be taken via any browser, including Chrome, Firefox, Safari, and Opera. This Microsoft AI-900 web-based practice exam does not require any other plugins. It also includes all of the functionalities of desktop AI-900 software and will assist you in passing the AI-900 certification test.

Microsoft AI-900, also known as Microsoft Azure AI Fundamentals, is a certification exam that validates an individual's knowledge and understanding of artificial intelligence and machine learning concepts and their application in cloud-based solutions using Microsoft Azure services. AI-900 Exam is designed to help individuals demonstrate their foundational knowledge of AI and its potential uses in business settings. Microsoft Azure AI Fundamentals certification is ideal for individuals who are new to AI and machine learning or want to gain expertise in the latest AI technologies.

Microsoft Azure AI Fundamentals Sample Questions (Q35-Q40):

NEW QUESTION # 35
You need to create a clustering model and evaluate the model by using Azure Machine Learning designer.
What should you do?

A. Use the original dataset for training and evaluation.
B. Split the original dataset into a dataset for training and a dataset for testing. Use the training dataset for evaluation.
C. Split the original dataset into a dataset for training and a dataset for testing. Use the testing dataset for evaluation.
D. Split the original dataset into a dataset for features and a dataset for labels. Use the features dataset for evaluation.

Answer: C

NEW QUESTION # 36
To complete the sentence, select the appropriate option in the answer area.

Answer:

Explanation:

Explanation:

Accelerate your business processes by automating information extraction. Form Recognizer applies advanced machine learning to accurately extract text, key/value pairs, and tables from documents. With just a few samples, Form Recognizer tailors its understanding to your documents, both on-premises and in the cloud.
Turn forms into usable data at a fraction of the time and cost, so you can focus more time acting on the information rather than compiling it.
Reference:
https://azure.microsoft.com/en-us/services/cognitive-services/form-recognizer/

NEW QUESTION # 37
You have a dataset that contains information about taxi journeys that occurred during a given period.
You need to train a model to predict the fare of a taxi journey. What should you use as a feature?

A. the trip distance of individual taxi journeys
B. the fare of individual taxi journeys
C. the number of taxi journeys in the dataset
D. the trip ID of individual taxi journeys

Answer: A

Explanation:
The label is the column you want to predict. The identified Featuresare the inputs you give the model to predict the Label.
Example:
The provided data set contains the following columns:
passenger_count: The number of passengers on the trip is a feature.
trip_time_in_secs: The amount of time the trip took. You want to predict the fare of the trip before the trip is completed. At that moment, you don't know how long the trip would take. Thus, the trip time is not a feature and you'll exclude this column from the model.
trip_distance: The distance of the trip is a feature.
payment_type: The payment method (cash or credit card) is a feature. fare_amount: The total taxi fare paid is the label.
Reference:
https://docs.microsoft.com/en-us/dotnet/machine-learning/tutorials/predict-prices

NEW QUESTION # 38
Select the answer that correctly completes the sentence.

Answer:

Explanation:

NEW QUESTION # 39
You need to provide customers with the ability to query the status of orders by using phones, social media, or digital assistants.
What should you use?

A. an Azure Machine Learning model
B. the Azure Al Translator service
C. an Azure Al Document Intelligence model
D. Azure Al Bot Service

Answer: A

NEW QUESTION # 40
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AI-900 Exam Demo, Answers AI-900 Free

Selecting AI-900 Exam Demo - Say Goodbye to Microsoft Azure AI Fundamentals

Microsoft Azure AI Fundamentals Sample Questions (Q35-Q40):

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