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Real AI-900 Braindumps | AI-900 New Dumps Ppt

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The Microsoft AI-900 exam has been created to cater to individuals who have little or no experience in AI or Azure, but are interested in developing a foundational understanding of the concepts. AI-900 exam focuses on providing a thorough understanding of the basics of AI and its applications in different industries, such as healthcare, finance, and retail.

The Microsoft Azure AI Fundamentals certification exam is an excellent starting point for individuals who are interested in pursuing a career in AI and ML. It will help them gain a fundamental understanding of the core concepts and principles of AI and ML, as well as develop the necessary skills to work with Azure's AI and ML services. AI-900 Exam is also suitable for professionals who work in IT, data science, and other related fields, as it will help them broaden their knowledge and skill set in AI and ML.

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Microsoft Azure AI Fundamentals Sample Questions (Q63-Q68):

NEW QUESTION # 63
Which machine learning technique can be used for anomaly detection?

A. A machine learning technique that analyzes data over time and identifies unusual changes.
B. A machine learning technique that understands written and spoken language.
C. A machine learning technique that classifies images based on their contents.
D. A machine learning technique that classifies objects based on user supplied images.

Answer: A

Explanation:
According to the Microsoft Azure AI Fundamentals (AI-900) Official Study Guide and the Microsoft Learn module "Explore fundamental principles of machine learning," anomaly detection is a specialized machine learning technique used to identify data points, patterns, or events that deviate significantly from normal behavior.
Anomaly detection is widely used for monitoring time-series data and detecting unexpected or rare occurrences that may indicate problems, opportunities, or fraud. For example:
* Detecting fraudulent transactions in banking systems.
* Identifying equipment malfunctions in industrial IoT applications.
* Monitoring network intrusions in cybersecurity.
* Detecting unexpected spikes or drops in web traffic or sales.
In Azure, this workload is supported by the Azure AI Anomaly Detector service, which uses statistical and machine learning algorithms to learn from historical data and establish a baseline of normal behavior. When the system detects data points that fall outside expected patterns, it flags them as anomalies.
Let's evaluate the incorrect options:
* A. A machine learning technique that understands written and spoken language # This describes Natural Language Processing (NLP), not anomaly detection.
* B. A machine learning technique that classifies objects based on user-supplied images # This refers to image classification, typically using computer vision.
* D. A machine learning technique that classifies images based on their contents # Also describes computer vision, not anomaly detection.
Therefore, the correct answer is C, since anomaly detection specifically refers to analyzing data over time and identifying unusual or abnormal patterns that differ from the expected trend.

NEW QUESTION # 64
You are authoring a Language Understanding (LUIS) application to support a music festival.
You want users to be able to ask questions about scheduled shows, such as: "Which act is playing on the main stage?" The question "Which act is playing on the main stage?" is an example of which type of element?

A. an intent
B. an utterance
C. an entity
D. a domain

Answer: B

Explanation:
Utterances are input from the user that your app needs to interpret.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/LUIS/luis-concept-utterance

NEW QUESTION # 65
Match the tool to the Azure Machine Learning task.
To answer, drag the appropriate tool from the column on the left to its tasks on the right. Each tool may be used once, more than once, or not at all NOTE: Each correct match is worth one point.

Answer:

Explanation:
Explanation

NEW QUESTION # 66
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Reference:
https://azure.microsoft.com/es-es/blog/machine-assisted-text-classification-on-content-moderator-public-preview/
https://docs.microsoft.com/en-us/azure/architecture/data-guide/technology-choices/natural-language-processing

NEW QUESTION # 67
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point.

Answer:

Explanation:

Explanation:
Box 1: Yes
Automated machine learning, also referred to as automated ML or AutoML, is the process of automating the time consuming, iterative tasks of machine learning model development. It allows data scientists, analysts, and developers to build ML models with high scale, efficiency, and productivity all while sustaining model quality.
Box 2: No
Box 3: Yes
During training, Azure Machine Learning creates a number of pipelines in parallel that try different algorithms and parameters for you. The service iterates through ML algorithms paired with feature selections, where each iteration produces a model with a training score. The higher the score, the better the model is considered to "fit" your data. It will stop once it hits the exit criteria defined in the experiment.
Box 4: No
Apply automated ML when you want Azure Machine Learning to train and tune a model for you using the target metric you specify.
The label is the column you want to predict.
Reference:
https://azure.microsoft.com/en-us/services/machine-learning/automatedml/#features

NEW QUESTION # 68
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