[Aug 2021] The latest update of Lead4Pass AI-900 exam dumps provides PDF and VCE

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Microsoft AI-900 exam questions and answers online practice test from Lead4Pass

QUESTION 1
DRAG DROP
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.
Select and Place:microsoft ai-900 exam questions q1

Box 1: Regression
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.
Box 2: Classification
Classification is a machine learning method that uses data to determine the category, type, or class of an item or row of
data.
Box 3: Clustering
Clustering, in machine learning, is a method of grouping data points into similar clusters. It is also called segmentation.
Over the years, many clustering algorithms have been developed. Almost all clustering algorithms use the features of
individual items to find similar items. For example, you might apply clustering to find similar people by demographics.
You
might use clustering with text analysis to group sentences with similar topics or sentiment.
Reference: https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/linear-regression

 

QUESTION 2
Which metric can you use to evaluate a classification model?
A. true positive rate
B. mean absolute error (MAE)
C. coefficient of determination (R2)
D. root mean squared error (RMSE)
Correct Answer: A
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

 

QUESTION 3
HOTSPOT
To complete the sentence, select the appropriate option in the answer area.
Hot Area:microsoft ai-900 exam questions q3

Correct Answer:

microsoft ai-900 exam questions q3-1

With Microsoft\\’s Conversational AI tools developers can build, connect, deploy, and manage intelligent bots that
naturally interact with their users on a website, app, Cortana, Microsoft Teams, Skype, Facebook Messenger, Slack,
and more.
Reference: https://azure.microsoft.com/en-in/blog/microsoft-conversational-ai-tools-enable-developers-to-build-connectand-manage-intelligent-bots

 

QUESTION 4
DRAG DROP
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.
Select and Place:microsoft ai-900 exam questions q4

Correct Answer:

microsoft ai-900 exam questions q4-1

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

 

QUESTION 5
You need to determine the location of cars in an image so that you can estimate the distance between the cars. Which
type of computer vision should you use?
A. optical character recognition (OCR)
B. object detection
C. image classification
D. face detection
Correct Answer: B
Object detection is similar to tagging, but the API returns the bounding box coordinates (in pixels) for each object found.
For example, if an image contains a dog, cat and person, the Detect operation will list those objects together with their
coordinates in the image. You can use this functionality to process the relationships between the objects in an image. It
also lets you determine whether there are multiple instances of the same tag in an image.
The Detect API applies tags based on the objects or living things identified in the image. There is currently no formal
relationship between the tagging taxonomy and the object detection taxonomy. At a conceptual level, the Detect API
only finds objects and living things, while the Tag API can also include contextual terms like “indoor”, which can\\’t be
localized with bounding boxes.
Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/concept-object-detection

 

QUESTION 6
What are three Microsoft guiding principles for responsible AI? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A. knowledgeability
B. decisiveness
C. inclusiveness
D. fairness
E. opinionatedness
F. reliability and safety
Correct Answer: CDF
Reference: https://docs.microsoft.com/en-us/learn/modules/responsible-ai-principles/4-guiding-principles

 

QUESTION 7
HOTSPOT
To complete the sentence, select the appropriate option in the answer area.
Hot Area:microsoft ai-900 exam questions q7

Correct Answer:

microsoft ai-900 exam questions q7-1

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/

 

QUESTION 8
You need to reduce the load on telephone operators by implementing a chatbot to answer simple questions with
predefined answers.
Which two AI service should you use to achieve the goal? Each correct answer presents part of the solution.
NOTE: Each correct selection is worth one point.
A. Text Analytics
B. QnA Maker
C. Azure Bot Service
D. Translator Text
Correct Answer: BC
Bots are a popular way to provide support through multiple communication channels. You can use the QnA Maker
service and Azure Bot Service to create a bot that answers user questions.
Reference: https://docs.microsoft.com/en-us/learn/modules/build-faq-chatbot-qna-maker-azure-bot-service/

 

QUESTION 9
In which two scenarios can you use the Form Recognizer service? Each correct answer presents a complete solution.
NOTE: Each correct selection is worth one point.
A. Extract the invoice number from an invoice.
B. Translate a form from French to English.
C. Find image of product in a catalog.
D. Identity the retailer from a receipt.
Correct Answer: AD
Reference: https://azure.microsoft.com/en-gb/services/cognitive-services/form-recognizer/#features

 

QUESTION 10
HOTSPOT
To complete the sentence, select the appropriate option in the answer area.
Hot Area:microsoft ai-900 exam questions q10

Correct Answer:

microsoft ai-900 exam questions q10-1

Reference: https://azure.microsoft.com/en-gb/services/cognitive-services/speech-to-text/#features

 

QUESTION 11
What are two tasks that can be performed by using the Computer Vision service? Each correct answer presents a
complete solution. NOTE: Each correct selection is worth one point.
A. Train a custom image classification model.
B. Detect faces in an image.
C. Recognize handwritten text.
D. Translate the text in an image between languages.
Correct Answer: BC
B: Azure\\’s Computer Vision service provides developers with access to advanced algorithms that process images and
return information based on the visual features you\\’re interested in. For example, Computer Vision can determine
whether an image contains adult content, find specific brands or objects, or find human faces.
C: Computer Vision includes Optical Character Recognition (OCR) capabilities. You can use the new Read API to
extract printed and handwritten text from images and documents.
Reference: https://docs.microsoft.com/en-us/azure/cognitive-services/computer-vision/home

 

QUESTION 12
HOTSPOT
To complete the sentence, select the appropriate option in the answer area.
Hot Area:microsoft ai-900 exam questions q12

Azure Custom Vision is a cognitive service that lets you build, deploy, and improve your own image classifiers. An
image classifier is an AI service that applies labels (which represent classes) to images, according to their visual
characteristics. Unlike the Computer Vision service, Custom Vision allows you to specify the labels to apply.
Note: The Custom Vision service uses a machine learning algorithm to apply labels to images. You, the developer, must
submit groups of images that feature and lack the characteristics in question. You label the images yourself at the time
of
submission. Then the algorithm trains to this data and calculates its own accuracy by testing itself on those same
images. Once the algorithm is trained, you can test, retrain, and eventually use it to classify new images according to
the needs
of your app. You can also export the model itself for offline use.
Incorrect Answers:
Computer Vision:
Azure\\’s Computer Vision service provides developers with access to advanced algorithms that process images and
return information based on the visual features you\\’re interested in. For example, Computer Vision can determine
whether an
image contains adult content, find specific brands or objects, or find human faces.
Reference:
https://docs.microsoft.com/en-us/azure/cognitive-services/custom-vision-service/home

 

QUESTION 13
HOTSPOT
For each of the following statements, select Yes if the statement is true. Otherwise, select No.
NOTE: Each correct selection is worth one point. Hot Area:microsoft ai-900 exam questions q13

Correct Answer:

microsoft ai-900 exam questions q13-1

Anomaly detection encompasses many important tasks in machine learning:
Identifying transactions that are potentially fraudulent.
Learning patterns that indicate that a network intrusion has occurred.
Finding abnormal clusters of patients.
Checking values entered into a system.
Reference:
https://docs.microsoft.com/en-us/azure/machine-learning/studio-module-reference/anomaly-detection


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