Podcast
Questions and Answers
Match the types of AI workloads to the appropriate scenarios.
Match the types of AI workloads to the appropriate scenarios.
Knowledge mining = Populate knowledge base in chatbot Computer vision = Identify objects/letters Natural language processing = Sentiment analysis
Your company is exploring the use of voice recognition technologies in its smart home devices. The company wants to identify any barriers that might unintentionally leave out specific user groups. This is an example of which Microsoft guiding principle for responsible AI?
Your company is exploring the use of voice recognition technologies in its smart home devices. The company wants to identify any barriers that might unintentionally leave out specific user groups. This is an example of which Microsoft guiding principle for responsible AI?
What are three Microsoft guiding principles for responsible AI?
What are three Microsoft guiding principles for responsible AI?
When you design an AI system to assess whether loans should be approved, the factors used to make the decision should be __________. This is an example of which Microsoft guiding principle for responsible AI?
When you design an AI system to assess whether loans should be approved, the factors used to make the decision should be __________. This is an example of which Microsoft guiding principle for responsible AI?
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You run a charity event that involves posting photos of people wearing sunglasses on Twitter. You need to ensure that you only retweet photos that meet certain requirements. What should you use to analyze the images?
You run a charity event that involves posting photos of people wearing sunglasses on Twitter. You need to ensure that you only retweet photos that meet certain requirements. What should you use to analyze the images?
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Implementing Agile software development methodology is a Microsoft guiding principle for responsible AI.
Implementing Agile software development methodology is a Microsoft guiding principle for responsible AI.
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Which type of machine learning should you use to identify groups of people who have similar purchasing habits?
Which type of machine learning should you use to identify groups of people who have similar purchasing habits?
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Which two actions are performed during the data ingestion and data preparation stage of an Azure Machine Learning process?
Which two actions are performed during the data ingestion and data preparation stage of an Azure Machine Learning process?
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You need to predict the animal population of an area. Which Azure Machine Learning type should you use?
You need to predict the animal population of an area. Which Azure Machine Learning type should you use?
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A company employs a team of customer service agents to provide telephone and email support to customers. The company develops a webchat bot to provide automated answers to common customer queries. Which business benefit should the company expect as a result of creating the webchat bot solution?
A company employs a team of customer service agents to provide telephone and email support to customers. The company develops a webchat bot to provide automated answers to common customer queries. Which business benefit should the company expect as a result of creating the webchat bot solution?
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For a machine learning progress, how should you split data for training and evaluation?
For a machine learning progress, how should you split data for training and evaluation?
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You build a machine learning model by using the automated machine learning user interface. You need to ensure that the model meets the Microsoft transparency principle for responsible AI. What should you do?
You build a machine learning model by using the automated machine learning user interface. You need to ensure that the model meets the Microsoft transparency principle for responsible AI. What should you do?
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To complete the sentence, select the appropriate option in the answer area.
To complete the sentence, select the appropriate option in the answer area.
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Match the types of AI workloads to the appropriate scenarios.
Match the types of AI workloads to the appropriate scenarios.
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You are designing an AI system that empowers everyone, including people with hearing, visual, and other impairments. This is an example of which Microsoft guiding principle for responsible AI?
You are designing an AI system that empowers everyone, including people with hearing, visual, and other impairments. This is an example of which Microsoft guiding principle for responsible AI?
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Match the Microsoft guiding principles for responsible AI to the appropriate descriptions.
Match the Microsoft guiding principles for responsible AI to the appropriate descriptions.
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To complete the sentence, select the appropriate option in the answer area.
To complete the sentence, select the appropriate option in the answer area.
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You are building an AI system. Which task should you include to ensure that the service meets the Microsoft transparency principle for responsible AI?
You are building an AI system. Which task should you include to ensure that the service meets the Microsoft transparency principle for responsible AI?
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You have the Predicted vs. True chart shown in the following exhibit. Which type of model is the chart used to evaluate?
You have the Predicted vs. True chart shown in the following exhibit. Which type of model is the chart used to evaluate?
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Which type of machine learning should you use to predict the number of gift cards that will be sold next month?
Which type of machine learning should you use to predict the number of gift cards that will be sold next month?
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You need to predict the sea level in meters for the next 10 years. Which type of machine learning should you use?
You need to predict the sea level in meters for the next 10 years. Which type of machine learning should you use?
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Which service should you use to extract text, key/value pairs, and table data automatically from scanned documents?
Which service should you use to extract text, key/value pairs, and table data automatically from scanned documents?
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You use Azure Machine Learning designer to publish an inference pipeline. Which two parameters should you use to access the web service?
You use Azure Machine Learning designer to publish an inference pipeline. Which two parameters should you use to access the web service?
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You have insurance claim reports that are stored as text. You need to extract key terms from the reports to generate summaries. Which type of AI workload should you use?
You have insurance claim reports that are stored as text. You need to extract key terms from the reports to generate summaries. Which type of AI workload should you use?
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To complete the sentence, select the appropriate option: Natural language processing (NLP) is used for tasks such as sentiment analysis, topic detection, language detection, key phrase extraction, and document categorization.
To complete the sentence, select the appropriate option: Natural language processing (NLP) is used for tasks such as sentiment analysis, topic detection, language detection, key phrase extraction, and document categorization.
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Which AI service can you use to interpret the meaning of a user input such as Call me back later
?
Which AI service can you use to interpret the meaning of a user input such as Call me back later
?
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You are developing a chatbot solution in Azure. Which service should you use to determine a user's intent?
You are developing a chatbot solution in Azure. Which service should you use to determine a user's intent?
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You need to make the written press releases of your company available in a range of languages. Which service should you use?
You need to make the written press releases of your company available in a range of languages. Which service should you use?
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A medical research project aims to detect different brain hemorrhage types in images using machine learning. What type of machine learning is this example?
A medical research project aims to detect different brain hemorrhage types in images using machine learning. What type of machine learning is this example?
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When training a model, why should you randomly split the rows into separate subsets?
When training a model, why should you randomly split the rows into separate subsets?
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You are building a tool to identify competitor products in images from retail stores using a custom model. Which Azure Cognitive Service should you use?
You are building a tool to identify competitor products in images from retail stores using a custom model. Which Azure Cognitive Service should you use?
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What are two metrics that can be used to evaluate a regression model?
What are two metrics that can be used to evaluate a regression model?
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Which two languages can you use to write custom code for Azure Machine Learning designer?
Which two languages can you use to write custom code for Azure Machine Learning designer?
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Your company wants to build a recycling machine for bottles. Which type of AI workload should the company use?
Your company wants to build a recycling machine for bottles. Which type of AI workload should the company use?
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In which two scenarios can you use the Form Recognizer service?
In which two scenarios can you use the Form Recognizer service?
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You need to develop a mobile app for employees to scan and store their expenses while traveling. Which type of computer vision should you use?
You need to develop a mobile app for employees to scan and store their expenses while traveling. Which type of computer vision should you use?
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You are processing photos of runners in a race. You need to read the numbers on the runners' shirts to identity the runners in the photos. Which type of computer vision should you use?
You are processing photos of runners in a race. You need to read the numbers on the runners' shirts to identity the runners in the photos. Which type of computer vision should you use?
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You use drones to identify where weeds grow between rows of crops to send an instruction for the removal of the weeds. This is an example of which type of computer vision?
You use drones to identify where weeds grow between rows of crops to send an instruction for the removal of the weeds. This is an example of which type of computer vision?
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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?
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?
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What are two tasks that can be performed by using the Computer Vision service?
What are two tasks that can be performed by using the Computer Vision service?
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What is a use case for classification?
What is a use case for classification?
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What are two tasks that can be performed by using computer vision?
What are two tasks that can be performed by using computer vision?
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You need to build an image tagging solution for social media that tags images of your friends automatically. Which Azure Cognitive Services service should you use?
You need to build an image tagging solution for social media that tags images of your friends automatically. Which Azure Cognitive Services service should you use?
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In which two scenarios can you use the Form Recognizer service?
In which two scenarios can you use the Form Recognizer service?
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Which Computer Vision feature can you use to generate automatic captions for digital photographs?
Which Computer Vision feature can you use to generate automatic captions for digital photographs?
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Which service should you use to extract text, key/value pairs, and table data automatically from scanned documents?
Which service should you use to extract text, key/value pairs, and table data automatically from scanned documents?
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You are developing a solution that uses the Text Analytics service. You need to identify the main talking points in a collection of documents. Which type of natural language processing should you use?
You are developing a solution that uses the Text Analytics service. You need to identify the main talking points in a collection of documents. Which type of natural language processing should you use?
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In which two scenarios can you use speech recognition?
In which two scenarios can you use speech recognition?
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You need to build an app that will read recipe instructions aloud to support users who have reduced vision. Which service should you use?
You need to build an app that will read recipe instructions aloud to support users who have reduced vision. Which service should you use?
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Your website has a chatbot to assist customers. You need to detect when a customer is upset based on what the customer types in the chatbot. Which type of AI workload should you use?
Your website has a chatbot to assist customers. You need to detect when a customer is upset based on what the customer types in the chatbot. Which type of AI workload should you use?
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You plan to develop a bot that will enable users to query a knowledge base by using natural language processing. Which two services should you include in the solution?
You plan to develop a bot that will enable users to query a knowledge base by using natural language processing. Which two services should you include in the solution?
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In which two scenarios can you use a speech synthesis solution?
In which two scenarios can you use a speech synthesis solution?
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You are building a knowledge base by using QnA Maker. Which file format can you use to populate the knowledge base?
You are building a knowledge base by using QnA Maker. Which file format can you use to populate the knowledge base?
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In which scenario should you use key phrase extraction?
In which scenario should you use key phrase extraction?
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Which type of machine learning should you use to identify groups of people who have similar purchasing habits?
Which type of machine learning should you use to identify groups of people who have similar purchasing habits?
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Which metric can you use to evaluate a classification model?
Which metric can you use to evaluate a classification model?
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Which two components can you drag onto a canvas in Azure Machine Learning designer?
Which two components can you drag onto a canvas in Azure Machine Learning designer?
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You need to create a training dataset and validation dataset from an existing dataset. Which module in the Azure Machine Learning designer should you use?
You need to create a training dataset and validation dataset from an existing dataset. Which module in the Azure Machine Learning designer should you use?
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You have the Predicted vs. True chart shown. Which type of model is the chart used to evaluate?
You have the Predicted vs. True chart shown. Which type of model is the chart used to evaluate?
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Which type of machine learning should you use to predict the number of gift cards that will be sold next month?
Which type of machine learning should you use to predict the number of gift cards that will be sold next month?
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You have a dataset on taxi journeys. What should you use as a feature to predict the fare of a taxi journey?
You have a dataset on taxi journeys. What should you use as a feature to predict the fare of a taxi journey?
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You need to predict the sea level for the next 10 years. Which type of machine learning should you use?
You need to predict the sea level for the next 10 years. Which type of machine learning should you use?
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Which service should you use to extract text, key/value pairs, and table data from scanned documents?
Which service should you use to extract text, key/value pairs, and table data from scanned documents?
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You are publishing an inference pipeline in Azure ML designer. Which parameters should you use to access the web service?
You are publishing an inference pipeline in Azure ML designer. Which parameters should you use to access the web service?
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In a medical research project focusing on brain hemorrhage detection, what type of machine learning is used for early detection of brain hemorrhage types in images?
In a medical research project focusing on brain hemorrhage detection, what type of machine learning is used for early detection of brain hemorrhage types in images?
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What tasks require an enterprise workspace in Azure Machine Learning?
What tasks require an enterprise workspace in Azure Machine Learning?
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Which fields should be used as features to predict the income range of a customer?
Which fields should be used as features to predict the income range of a customer?
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For processing retail store images and identifying competitor products using a custom model, which Azure Cognitive Services should be used?
For processing retail store images and identifying competitor products using a custom model, which Azure Cognitive Services should be used?
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Which metrics can be used to evaluate a regression model?
Which metrics can be used to evaluate a regression model?
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A company develops a webchat bot to provide automated answers to common customer queries. What business benefit should the company expect as a result of creating the webchat bot solution?
A company develops a webchat bot to provide automated answers to common customer queries. What business benefit should the company expect as a result of creating the webchat bot solution?
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For a machine learning project, how should you split data for training and evaluation?
For a machine learning project, how should you split data for training and evaluation?
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When designing a machine learning model using the automated machine learning UI, how can you ensure the model meets the Microsoft transparency principle for responsible AI?
When designing a machine learning model using the automated machine learning UI, how can you ensure the model meets the Microsoft transparency principle for responsible AI?
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Inclusiveness, as a Microsoft guiding principle for responsible AI, focuses on empowering everyone, including people with impairments. What does this principle emphasize?
Inclusiveness, as a Microsoft guiding principle for responsible AI, focuses on empowering everyone, including people with impairments. What does this principle emphasize?
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When building an AI system to meet the Microsoft transparency principle for responsible AI, which task should be included?
When building an AI system to meet the Microsoft transparency principle for responsible AI, which task should be included?
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You have insurance claim reports that are stored as text. You need to extract key terms from the reports to generate summaries. Which type of AI workload should you use?
You have insurance claim reports that are stored as text. You need to extract key terms from the reports to generate summaries. Which type of AI workload should you use?
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Which AI service can you use to interpret the meaning of a user input such as Call me back later
?
Which AI service can you use to interpret the meaning of a user input such as Call me back later
?
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You are developing a chatbot solution in Azure. Which service should you use to determine a user's intent?
You are developing a chatbot solution in Azure. Which service should you use to determine a user's intent?
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You need to make the written press releases of your company available in a range of languages. Which service should you use?
You need to make the written press releases of your company available in a range of languages. Which service should you use?
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Which two languages can you use to write custom code for Azure Machine Learning designer?
Which two languages can you use to write custom code for Azure Machine Learning designer?
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Your company wants to build a recycling machine for bottles. Which type of AI workload should the company use?
Your company wants to build a recycling machine for bottles. Which type of AI workload should the company use?
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In which two scenarios can you use the Form Recognizer service?
In which two scenarios can you use the Form Recognizer service?
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You need to develop a mobile app for employees to scan and store their expenses while traveling. Which type of computer vision should you use?
You need to develop a mobile app for employees to scan and store their expenses while traveling. Which type of computer vision should you use?
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You are processing photos of runners in a race. You need to read the numbers on the runners' shirts to identify the runners in the photos. Which type of computer vision should you use?
You are processing photos of runners in a race. You need to read the numbers on the runners' shirts to identify the runners in the photos. Which type of computer vision should you use?
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You use drones to identify where weeds grow between rows of crops to send an instruction for the removal of the weeds. This is an example of which type of computer vision?
You use drones to identify where weeds grow between rows of crops to send an instruction for the removal of the weeds. This is an example of which type of computer vision?
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Match the types of computer vision workloads to the appropriate scenarios.
Match the types of computer vision workloads to the appropriate scenarios.
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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?
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?
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To complete the sentence, select the appropriate option in the answer area.
To complete the sentence, select the appropriate option in the answer area.
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You send an image to a Computer Vision API and receive back the annotated image shown. Which type of computer vision was used?
You send an image to a Computer Vision API and receive back the annotated image shown. Which type of computer vision was used?
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What are two tasks that can be performed by using the Computer Vision service?
What are two tasks that can be performed by using the Computer Vision service?
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What is a use case for classification?
What is a use case for classification?
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What are two tasks that can be performed by using computer vision?
What are two tasks that can be performed by using computer vision?
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You need to build an image tagging solution for social media that tags images of your friends automatically. Which Azure Cognitive Services service should you use?
You need to build an image tagging solution for social media that tags images of your friends automatically. Which Azure Cognitive Services service should you use?
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In which two scenarios can you use the Form Recognizer service?
In which two scenarios can you use the Form Recognizer service?
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Match the facial recognition tasks to the appropriate questions.
Match the facial recognition tasks to the appropriate questions.
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Which Computer Vision feature can you use to generate automatic captions for digital photographs?
Which Computer Vision feature can you use to generate automatic captions for digital photographs?
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Which service should you use to extract text, key/value pairs, and table data automatically from scanned documents?
Which service should you use to extract text, key/value pairs, and table data automatically from scanned documents?
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You are developing a solution that uses the Text Analytics service. You need to identify the main talking points in a collection of documents. Which type of natural language processing should you use?
You are developing a solution that uses the Text Analytics service. You need to identify the main talking points in a collection of documents. Which type of natural language processing should you use?
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In which two scenarios can you use speech recognition?
In which two scenarios can you use speech recognition?
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You need to build an app that will read recipe instructions aloud to support users who have reduced vision. Which version service should you use?
You need to build an app that will read recipe instructions aloud to support users who have reduced vision. Which version service should you use?
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Your website has a chatbot to assist customers. You need to detect when a customer is upset based on what the customer types in the chatbot. Which type of AI workload should you use?
Your website has a chatbot to assist customers. You need to detect when a customer is upset based on what the customer types in the chatbot. Which type of AI workload should you use?
Signup and view all the answers
You plan to develop a bot that will enable users to query a knowledge base by using natural language processing. Which two services should you include in the solution?
You plan to develop a bot that will enable users to query a knowledge base by using natural language processing. Which two services should you include in the solution?
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In which two scenarios can you use a speech synthesis solution?
In which two scenarios can you use a speech synthesis solution?
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You are building a knowledge base by using QnA Maker. Which file format can you use to populate the knowledge base?
You are building a knowledge base by using QnA Maker. Which file format can you use to populate the knowledge base?
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In which scenario should you use key phrase extraction?
In which scenario should you use key phrase extraction?
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Your company is exploring the use of voice recognition technologies in its smart home devices. The company wants to identify any barriers that might unintentionally leave out specific user groups. This is an example of which Microsoft guiding principle for responsible AI?
Your company is exploring the use of voice recognition technologies in its smart home devices. The company wants to identify any barriers that might unintentionally leave out specific user groups. This is an example of which Microsoft guiding principle for responsible AI?
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What are three Microsoft guiding principles for responsible AI?
What are three Microsoft guiding principles for responsible AI?
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You run a charity event that involves posting photos of people wearing sunglasses on Twitter. You need to ensure that you only retweet photos that meet certain requirements. What should you use to analyze the images?
You run a charity event that involves posting photos of people wearing sunglasses on Twitter. You need to ensure that you only retweet photos that meet certain requirements. What should you use to analyze the images?
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When you design an AI system to assess whether loans should be approved, the factors used to make the decision should be explainable. This is an example of which Microsoft guiding principle for responsible AI?
When you design an AI system to assess whether loans should be approved, the factors used to make the decision should be explainable. This is an example of which Microsoft guiding principle for responsible AI?
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You are building an AI-based app. You need to ensure that the app uses the principles for responsible AI. Which two principles should you follow?
You are building an AI-based app. You need to ensure that the app uses the principles for responsible AI. Which two principles should you follow?
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Study Notes
Microsoft Azure AI Fundamentals
- A company employs a team of customer service agents to provide telephone and email support to customers.
- Creating a webchat bot to provide automated answers to common customer queries can lead to a reduced workload for the customer service agents.
Machine Learning
- For a machine learning process, it's recommended to split data into rows for training and rows for evaluation.
- The Split Data module is useful for separating data into training and testing sets.
- You can specify the percentage of data to put in each split, but by default, the data is divided 50-50.
- You can also randomize the selection of rows in each group, and use stratified sampling.
Classification
- In a confusion matrix, True Positive (TP) refers to the class labels in the training set that can take on only two possible values, which are positive or negative.
- False Negative (FN) refers to the incorrectly classified instances.
Model Explainability
- The automated machine learning user interface (UI) enables model explainability, which is critical for building trust and transparency in AI systems.
- Model explainability helps to understand the relationship between input variables (features) and model output.
- It's essential to comply with regulations and best practices, especially in heavily regulated industries like healthcare and banking.
Anomaly Detection
- Anomaly detection encompasses various important tasks in machine learning, such as:
- Identifying transactions that are potentially fraudulent.
- Learning patterns that indicate a network intrusion has occurred.
- Finding abnormal clusters of patients.
- Checking values entered into a system.
Natural Language Processing (NLP)
- NLP is used for tasks such as:
- Sentiment analysis
- Topic detection
- Language detection
- Key phrase extraction
- Document categorization
- NLP enables software to:
- Analyze text documents to extract key phrases and recognize entities.
- Perform sentiment analysis to determine the positivity or negativity of language used.
- Interpret spoken language and synthesize speech responses.
- Automatically translate spoken or written phrases between languages.
Microsoft Guiding Principles for Responsible AI
- The principles include:
- Fairness
- Inclusiveness
- Transparency
- Privacy and Security
- Reliability and Safety
- Accountability
- Inclusiveness means that AI systems should be designed to incorporate and address a broad range of human needs and experiences.
- Reliability and Safety ensure that AI systems operate reliably, safely, and consistently under normal circumstances and in unexpected conditions.
Feature Engineering
- Feature engineering is applied to generate additional features, and then feature selection is done to eliminate irrelevant, redundant, or highly correlated features.### Azure Machine Learning
- Azure Machine Learning is a cloud-based platform for building, training, and deploying machine learning models.
- It provides a range of tools and services for data scientists, developers, and business users to build, train, and deploy machine learning models.
Trusted AI
- Trusted AI is a set of principles and guidelines for building and deploying AI models that are responsible, reliable, and secure.
- It includes principles such as fairness, transparency, accountability, and explainability.
Responsible AI Principles
- There are four guiding principles for responsible AI: fairness, reliability, safety, and transparency.
- These principles are essential for building and deploying AI models that are trustworthy and responsible.
Machine Learning Tasks
- Machine learning tasks can be classified into three categories: classification, regression, and clustering.
- Classification involves predicting a categorical label or class.
- Regression involves predicting a continuous value or range.
- Clustering involves grouping similar data points into clusters.
Model Evaluation
- Model evaluation is an essential step in the machine learning workflow.
- It involves evaluating the performance of a model on a test dataset.
- Evaluation metrics include accuracy, precision, recall, F1 score, and mean squared error.
Azure Machine Learning Designer
- Azure Machine Learning Designer is a visual interface for building and deploying machine learning models.
- It allows users to create, train, and deploy models using a drag-and-drop interface.
- Users can connect datasets and modules to create a pipeline draft.
Inference Pipeline
- An inference pipeline is a pipeline that is used to make predictions on new data.
- It can be deployed as a real-time endpoint or a batch endpoint.
- Real-time endpoints are used for real-time inferencing, while batch endpoints are used for batch processing.
Automated Machine Learning
- Automated machine learning (AutoML) is a process that automates the machine learning workflow.
- It allows users to automate the selection of algorithms, hyperparameter tuning, and model training.
- AutoML is a no-code solution that can be used to build and deploy machine learning models.
Data Labeling
- Data labeling is the process of annotating data to prepare it for machine learning model training.
- It involves adding labels or annotations to the data to indicate the target value or class.
- Data labeling is an essential step in the machine learning workflow.
Form Recognizer
- Form Recognizer is a service that uses machine learning to extract text, key-value pairs, and tables from documents.
- It can be used to automate the extraction of information from documents.
- Form Recognizer is a part of the Azure Cognitive Services suite.
Prediction
- Prediction is the process of using a machine learning model to make predictions on new data.
- It involves using the trained model to make predictions on new, unseen data.
- Prediction is an essential step in the machine learning workflow.
Azure Kubernetes Service (AKS)
- AKS is a managed container orchestration service that allows users to deploy and manage containerized applications.
- It is used to deploy real-time endpoints for machine learning models.
- AKS provides a scalable and secure environment for deploying machine learning models.
Azure Container Service
- Azure Container Service is a managed container orchestration service that allows users to deploy and manage containerized applications.
- It is used to deploy machine learning models as a service.
- Azure Container Service provides a scalable and secure environment for deploying machine learning models.### Machine Learning Concepts
- Classification: A type of machine learning used to predict a label or category from a set of features. (Example: predicting brain haemorrhage types from brain scan images)
- Regression: A type of machine learning used to predict a numeric value from a set of features. (Example: predicting animal population)
- Clustering: A type of machine learning used to group instances of data into clusters with similar characteristics. (Example: identifying groups of people with similar purchasing habits)
Azure Machine Learning
- Automated ML: A type of machine learning that automatically selects and trains models for a given dataset.
- Designer: A visual interface for building machine learning models without writing code.
- Workspace: A container for machine learning projects, datasets, and models. (Basic and Enterprise workspaces are available)
Data Preparation and Ingestion
- Data Split: Divide a dataset into training and testing sets.
- Feature Engineering: The process of selecting and transforming raw data into features that are suitable for modeling.
- Data Ingestion: The process of loading data into a machine learning environment.
Model Evaluation
- Metrics: Used to evaluate the performance of a machine learning model. (Example: R2, RMSE, F1 score, AUC)
- Cross-Validation: A technique used to evaluate a model by splitting the data into multiple subsets and training/testing the model on each subset.
Azure Cognitive Services
- Custom Vision: A service that allows users to build, deploy, and improve custom image recognition models.
- Computer Vision: A service that provides pre-trained models for image analysis and processing.
Model Training and Deployment
- Training Dataset: A dataset used to train a machine learning model.
- Validation Dataset: A dataset used to evaluate the performance of a model during training.
- Testing Dataset: A dataset used to evaluate the final performance of a trained model.
- Deploying a Model: The process of deploying a trained model into a production environment.
Microsoft Azure AI Fundamentals
- A company employs a team of customer service agents to provide telephone and email support to customers.
- Creating a webchat bot to provide automated answers to common customer queries can lead to a reduced workload for the customer service agents.
Machine Learning
- For a machine learning process, it's recommended to split data into rows for training and rows for evaluation.
- The Split Data module is useful for separating data into training and testing sets.
- You can specify the percentage of data to put in each split, but by default, the data is divided 50-50.
- You can also randomize the selection of rows in each group, and use stratified sampling.
Classification
- In a confusion matrix, True Positive (TP) refers to the class labels in the training set that can take on only two possible values, which are positive or negative.
- False Negative (FN) refers to the incorrectly classified instances.
Model Explainability
- The automated machine learning user interface (UI) enables model explainability, which is critical for building trust and transparency in AI systems.
- Model explainability helps to understand the relationship between input variables (features) and model output.
- It's essential to comply with regulations and best practices, especially in heavily regulated industries like healthcare and banking.
Anomaly Detection
- Anomaly detection encompasses various important tasks in machine learning, such as:
- Identifying transactions that are potentially fraudulent.
- Learning patterns that indicate a network intrusion has occurred.
- Finding abnormal clusters of patients.
- Checking values entered into a system.
Natural Language Processing (NLP)
- NLP is used for tasks such as:
- Sentiment analysis
- Topic detection
- Language detection
- Key phrase extraction
- Document categorization
- NLP enables software to:
- Analyze text documents to extract key phrases and recognize entities.
- Perform sentiment analysis to determine the positivity or negativity of language used.
- Interpret spoken language and synthesize speech responses.
- Automatically translate spoken or written phrases between languages.
Microsoft Guiding Principles for Responsible AI
- The principles include:
- Fairness
- Inclusiveness
- Transparency
- Privacy and Security
- Reliability and Safety
- Accountability
- Inclusiveness means that AI systems should be designed to incorporate and address a broad range of human needs and experiences.
- Reliability and Safety ensure that AI systems operate reliably, safely, and consistently under normal circumstances and in unexpected conditions.
Feature Engineering
- Feature engineering is applied to generate additional features, and then feature selection is done to eliminate irrelevant, redundant, or highly correlated features.### Azure Machine Learning
- Azure Machine Learning is a cloud-based platform for building, training, and deploying machine learning models.
- It provides a range of tools and services for data scientists, developers, and business users to build, train, and deploy machine learning models.
Trusted AI
- Trusted AI is a set of principles and guidelines for building and deploying AI models that are responsible, reliable, and secure.
- It includes principles such as fairness, transparency, accountability, and explainability.
Responsible AI Principles
- There are four guiding principles for responsible AI: fairness, reliability, safety, and transparency.
- These principles are essential for building and deploying AI models that are trustworthy and responsible.
Machine Learning Tasks
- Machine learning tasks can be classified into three categories: classification, regression, and clustering.
- Classification involves predicting a categorical label or class.
- Regression involves predicting a continuous value or range.
- Clustering involves grouping similar data points into clusters.
Model Evaluation
- Model evaluation is an essential step in the machine learning workflow.
- It involves evaluating the performance of a model on a test dataset.
- Evaluation metrics include accuracy, precision, recall, F1 score, and mean squared error.
Azure Machine Learning Designer
- Azure Machine Learning Designer is a visual interface for building and deploying machine learning models.
- It allows users to create, train, and deploy models using a drag-and-drop interface.
- Users can connect datasets and modules to create a pipeline draft.
Inference Pipeline
- An inference pipeline is a pipeline that is used to make predictions on new data.
- It can be deployed as a real-time endpoint or a batch endpoint.
- Real-time endpoints are used for real-time inferencing, while batch endpoints are used for batch processing.
Automated Machine Learning
- Automated machine learning (AutoML) is a process that automates the machine learning workflow.
- It allows users to automate the selection of algorithms, hyperparameter tuning, and model training.
- AutoML is a no-code solution that can be used to build and deploy machine learning models.
Data Labeling
- Data labeling is the process of annotating data to prepare it for machine learning model training.
- It involves adding labels or annotations to the data to indicate the target value or class.
- Data labeling is an essential step in the machine learning workflow.
Form Recognizer
- Form Recognizer is a service that uses machine learning to extract text, key-value pairs, and tables from documents.
- It can be used to automate the extraction of information from documents.
- Form Recognizer is a part of the Azure Cognitive Services suite.
Prediction
- Prediction is the process of using a machine learning model to make predictions on new data.
- It involves using the trained model to make predictions on new, unseen data.
- Prediction is an essential step in the machine learning workflow.
Azure Kubernetes Service (AKS)
- AKS is a managed container orchestration service that allows users to deploy and manage containerized applications.
- It is used to deploy real-time endpoints for machine learning models.
- AKS provides a scalable and secure environment for deploying machine learning models.
Azure Container Service
- Azure Container Service is a managed container orchestration service that allows users to deploy and manage containerized applications.
- It is used to deploy machine learning models as a service.
- Azure Container Service provides a scalable and secure environment for deploying machine learning models.### Machine Learning Concepts
- Classification: A type of machine learning used to predict a label or category from a set of features. (Example: predicting brain haemorrhage types from brain scan images)
- Regression: A type of machine learning used to predict a numeric value from a set of features. (Example: predicting animal population)
- Clustering: A type of machine learning used to group instances of data into clusters with similar characteristics. (Example: identifying groups of people with similar purchasing habits)
Azure Machine Learning
- Automated ML: A type of machine learning that automatically selects and trains models for a given dataset.
- Designer: A visual interface for building machine learning models without writing code.
- Workspace: A container for machine learning projects, datasets, and models. (Basic and Enterprise workspaces are available)
Data Preparation and Ingestion
- Data Split: Divide a dataset into training and testing sets.
- Feature Engineering: The process of selecting and transforming raw data into features that are suitable for modeling.
- Data Ingestion: The process of loading data into a machine learning environment.
Model Evaluation
- Metrics: Used to evaluate the performance of a machine learning model. (Example: R2, RMSE, F1 score, AUC)
- Cross-Validation: A technique used to evaluate a model by splitting the data into multiple subsets and training/testing the model on each subset.
Azure Cognitive Services
- Custom Vision: A service that allows users to build, deploy, and improve custom image recognition models.
- Computer Vision: A service that provides pre-trained models for image analysis and processing.
Model Training and Deployment
- Training Dataset: A dataset used to train a machine learning model.
- Validation Dataset: A dataset used to evaluate the performance of a model during training.
- Testing Dataset: A dataset used to evaluate the final performance of a trained model.
- Deploying a Model: The process of deploying a trained model into a production environment.
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