What capability does facial detection provide in analyzing human faces in an image? Generate bounding boxes for objects Classify images based on content Detect and analyze human faces, including identifying a person's age Extract text from images

Detect and analyze human faces, including identifying a person's age

What are the limitations of language in relation to correct and features? Integration of language with correct, considering factors related to features Difficulty in real-time processing Inability to process large datasets Lack of semantic understanding

Integration of language with correct, considering factors related to features

Comprehensive AI and Machine Learning Concepts with Practical Applications

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Computer Science - Software Engineering

user_kambeorv Created by 7 mon ago

Cards in this deck(100)

Which artificial intelligence (AI) technique serves as the foundation for modern image classification solutions?

What process employs specialized algorithms to model and study complex datasets, establishing relationships among data?

Which technique provides the ability to classify individual pixels in an image depending on the object they represent?

Which statistical methods are used to predict numeric values by training and validating predictions?

Which computer vision solution provides the ability to identify a person's age based on a photograph?

What capability does facial detection provide in analyzing human faces in an image?

What is the process of classifying images based on their contents called?

Which technique provides the ability to generate bounding boxes identifying the locations of different types of vehicles in an image?

What are the limitations of language in relation to correct and features?

Which two specialized domain models are supported by Azure AI Vision when categorizing an image?

What can be used for an attendance system that can scan handwritten signatures?

What is used to extract text and handwriting from images?

Which technique can detect and verify human faces, not text, from images?

Which technique can detect multiple objects in an image by using bounding box coordinates?

Which feature of computer vision involves associating an image with metadata that summarizes the attributes of the image?

What involves associating an image with metadata that summarizes the attributes of the image?

What involves identifying clip art images or line drawings?

What involves identifying people or objects in photos and organizing them based on the identification?

What involves associating the contents of an image with a limited set of categories?

Which three parts of the machine learning process does the Azure AI Vision eliminate the need for?

Which analytical task of the Azure AI Vision service returns bounding box coordinates?

What identifies common objects and, for each, returns bounding box coordinates?

What assigns a category to an image but does not return bounding box coordinates?

What is the significance of image in relation to language and correct?

What detects printed and handwritten text in images?

Which two Azure AI Document Intelligence models include identifying common data fields as part of its data extraction capabilities?

When using the Azure AI Face service, what should you use to perform one-to-many or one-to-one face matching?

Which three sources can be used to generate questions and answers for a knowledge base?

Which feature uses plugins to provide end users with the ability to get help with common tasks from a generative AI model?

Which AI model can return responses, such as natural language, images, or code, based on natural language input?

What is the training of machine learning models to make a sequence of decisions called?

What can be used to identify constraints and styles for the responses of a generative AI model?

Which two capabilities are examples of a GPT model?

Which three capabilities are examples of image generation features for a generative AI model?

Which capability is NOT supported by the DALL-E model when developing an image processing solution?

What capabilities does the DALL-E model provide?

Which generative AI model is used to generate images based on natural language prompts?

Which models can understand and generate natural language and code but not images?

What can convert text into numerical vector form to facilitate text similarity?

What can transcribe and translate speech to text?

What can search, classify, and compare sources of text for similarity?

Which natural language processing (NLP) technique normalizes words before counting them?

What counts how often a word appears in a text?

What extends frequency analysis to include multi-term phrases?

What captures semantic relationships between words by assigning them to locations in n-dimensional space?

What is the first step in the statistical analysis of terms in a text in the context of natural language processing (NLP)?

Which two features of Azure AI Services allow you to identify issues from support question data, as well as identify any people and products that are mentioned?

What is used to extract key phrases to identify the main concepts in a text?

What can identify and categorize entities in unstructured text, such as people, places, organizations, and quantities?

Which Azure AI Service for Language feature allows you to analyze written articles to extract information and concepts, such as people and locations, for classification purposes?

Which three values are returned by the language detection feature of the Azure AI Language service in Azure?

For which two scenarios is the Universal Language Model used by the speech-to-text API optimized?

Which three features are elements of the Azure AI Language Service?

What is used to check text, image, and video content for material that is potentially offensive?

Which three features are elements of the Azure AI Speech service?

What are part of the Translator service?

When using the Azure AI Service for Language, what should you use to provide further information online about entities extracted from a text?

You need to identify numerical values that represent the probability of humans developing diabetes based on age and body fat percentage. Which type of machine learning model should you use?

What models a relationship between two or more features and a single label?

What is a type of classification model, which returns either a Boolean value or a categorical decision?

What groups data points that have similar characteristics?

What uses a single feature?

Which type of machine learning algorithm assigns items to a set of predefined categories?

What are used to predict numeric values?

What is a category of learning algorithms that includes clustering, but not regression or classification?

A healthcare organization has a dataset consisting of bone fracture scans that are categorized by using predefined fracture types. The organization wants to use machine learning to detect the different types of bone fractures for new scans before the scans are sent to a medical practitioner. Which type of machine learning is this?

What analyzes unlabeled data to find similarities in the data?

You plan to use machine learning to predict the probability of humans developing diabetes based on their age and body fat percentage. What should the model include?

What scenario involves two features (age and body fat percentage) and one label (the likelihood of developing diabetes)?

Which assumption of the multiple linear regression model should be satisfied to avoid misleading predictions?

What models the relationship between several features and a single label?

In a regression machine learning algorithm, what are the characteristics of features and labels in a validation dataset?

In a regression machine learning algorithm, what does a validation set contain?

A company is using machine learning to predict house prices based on appropriate house attributes. For the machine learning model, which attribute is the label?

A company wants to predict household water use based on the number of people in a house, the weather temperature, and the time of year. In terms of data labels and features, what is the label in this use case?

What is the purpose of a validation dataset used for as part of the development of a machine learning model?

What is part of preparing the dataset and related data transformation processes?

What is used to provide summary statistics, such as the mean or count of distinct values in a column?

What is used to detect missing values and perform operations to fix the data or create new values?

You need to use Azure Machine Learning to train a regression model. What should you create in Machine Learning studio?

What must be created before you can access Machine Learning studio?

What can be created as a deployment target, after training of a model is complete?

You need to use the Azure Machine Learning designer to deploy a predictive service from a newly trained model. What should you do first in the Machine Learning designer?

You train a regression model by using automated machine learning (automated ML) in the Azure Machine Learning studio. You review the best model summary. You need to publish the model for others to use from the internet. What should you do next?

What are used to train the model and are created directly after you create a Machine Learning workspace?

Which artificial intelligence (AI) workload scenario is an example of natural language processing (NLP)?

Which two artificial intelligence (AI) workload scenarios are examples of natural language processing (NLP)?

You are exploring solutions to improve the document search and indexing service for employees. You need an artificial intelligence (AI) search solution that will include searching text in various types of documents, such as images. Which type of AI workload is this?

What primarily focuses on the searching and indexing of data?

What is part of natural language processing (NLP) and facilitates the creation of chatbots?

How can you identify data in relation to used and which?

Which two artificial intelligence (AI) workload features are part of the Azure AI Vision service?

Which principle of responsible artificial intelligence (AI) raises awareness about the limitations of AI-based solutions?

Which principle of responsible artificial intelligence (AI) has the objective of ensuring that AI solutions benefit all parts of society regardless of gender or ethnicity?

Which principle of responsible artificial intelligence (AI) plays the primary role when implementing an AI solution that meets qualifications for business loan approvals?

What is meant to ensure that AI models do not unintentionally incorporate a bias based on criteria such as gender or ethnicity?

A bank is developing a new artificial intelligence (AI) system to support the process of accepting or rejecting mortgage applications. Which two issues should be considered as part of the responsible AI principle of fairness to avoid biased decision making?

Which two principles of responsible artificial intelligence (AI) are most important when designing an AI system to manage healthcare data?

What states that AI systems are designed to meet any ethical and legal standards that are applicable?

What states that AI systems must empower people in a positive and engaging way?

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