Microsoft Azure AI Fundamentals Quiz
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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?

  • Accountability
  • Privacy and security
  • Fairness
  • Inclusiveness (correct)
  • What are three Microsoft guiding principles for responsible AI?

  • Reliability and safety (correct)
  • Knowledgeability
  • Inclusiveness (correct)
  • Opinionatedness
  • Decisiveness
  • Fairness (correct)
  • 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?

    <p>explainable</p> Signup and view all the answers

    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?

    <p>The Detect operation in the Face service</p> Signup and view all the answers

    Implementing Agile software development methodology is a Microsoft guiding principle for responsible AI.

    <p>False</p> Signup and view all the answers

    Which type of machine learning should you use to identify groups of people who have similar purchasing habits?

    <p>Clustering</p> Signup and view all the answers

    Which two actions are performed during the data ingestion and data preparation stage of an Azure Machine Learning process?

    <p>CE</p> Signup and view all the answers

    You need to predict the animal population of an area. Which Azure Machine Learning type should you use?

    <p>Regression</p> Signup and view all the answers

    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?

    <p>A reduced workload for the customer service agents</p> Signup and view all the answers

    For a machine learning progress, how should you split data for training and evaluation?

    <p>Randomly split the data into rows for training and rows for evaluation</p> Signup and view all the answers

    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?

    <p>Enable Explain best model</p> Signup and view all the answers

    To complete the sentence, select the appropriate option in the answer area.

    <p>Reliability and safety</p> Signup and view all the answers

    Match the types of AI workloads to the appropriate scenarios.

    <p>Natural language processing = Sentiment analysis, key phrase extraction Image recognition = Identify objects in images Speech recognition = Convert spoken language to text Recommendation systems = Suggest products based on user behavior</p> Signup and view all the answers

    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?

    <p>Inclusiveness</p> Signup and view all the answers

    Match the Microsoft guiding principles for responsible AI to the appropriate descriptions.

    <p>Reliability and safety = Operate reliably under various conditions Accountability = Be accountable for system operation Privacy and security = Protect privacy and secure data</p> Signup and view all the answers

    To complete the sentence, select the appropriate option in the answer area.

    <p>Reliability and safety</p> Signup and view all the answers

    You are building an AI system. Which task should you include to ensure that the service meets the Microsoft transparency principle for responsible AI?

    <p>Ensure that a training dataset is representative of the population</p> Signup and view all the answers

    You have the Predicted vs. True chart shown in the following exhibit. Which type of model is the chart used to evaluate?

    <p>Regression</p> Signup and view all the answers

    Which type of machine learning should you use to predict the number of gift cards that will be sold next month?

    <p>Regression</p> Signup and view all the answers

    You need to predict the sea level in meters for the next 10 years. Which type of machine learning should you use?

    <p>Regression</p> Signup and view all the answers

    Which service should you use to extract text, key/value pairs, and table data automatically from scanned documents?

    <p>Form Recognizer</p> Signup and view all the answers

    You use Azure Machine Learning designer to publish an inference pipeline. Which two parameters should you use to access the web service?

    <p>The REST endpoint</p> Signup and view all the answers

    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?

    <p>Natural Language Processing</p> Signup and view all the answers

    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.

    <p>NLP</p> Signup and view all the answers

    Which AI service can you use to interpret the meaning of a user input such as Call me back later?

    <p>Language Understanding (LUIS)</p> Signup and view all the answers

    You are developing a chatbot solution in Azure. Which service should you use to determine a user's intent?

    <p>Language Understanding (LUIS)</p> Signup and view all the answers

    You need to make the written press releases of your company available in a range of languages. Which service should you use?

    <p>Translator</p> Signup and view all the answers

    A medical research project aims to detect different brain hemorrhage types in images using machine learning. What type of machine learning is this example?

    <p>Classification</p> Signup and view all the answers

    When training a model, why should you randomly split the rows into separate subsets?

    <p>To test the model by using data that was not used to train the model</p> Signup and view all the answers

    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?

    <p>Custom Vision</p> Signup and view all the answers

    What are two metrics that can be used to evaluate a regression model?

    <p>Root mean squared error (RMSE)</p> Signup and view all the answers

    Which two languages can you use to write custom code for Azure Machine Learning designer?

    <p>R</p> Signup and view all the answers

    Your company wants to build a recycling machine for bottles. Which type of AI workload should the company use?

    <p>Computer vision</p> Signup and view all the answers

    In which two scenarios can you use the Form Recognizer service?

    <p>Extract the invoice number from an invoice and Identify the retailer from a receipt</p> Signup and view all the answers

    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?

    <p>Optical character recognition (OCR)</p> Signup and view all the answers

    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?

    <p>Optical character recognition (OCR)</p> Signup and view all the answers

    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?

    <p>Object detection</p> Signup and view all the answers

    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?

    <p>Object detection</p> Signup and view all the answers

    What are two tasks that can be performed by using the Computer Vision service?

    <p>Recognize handwritten text</p> Signup and view all the answers

    What is a use case for classification?

    <p>Predicting whether someone uses a bicycle to travel to work based on the distance from home to work</p> Signup and view all the answers

    What are two tasks that can be performed by using computer vision?

    <p>Detect brands in an image</p> Signup and view all the answers

    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?

    <p>Face</p> Signup and view all the answers

    In which two scenarios can you use the Form Recognizer service?

    <p>Extract the invoice number from an invoice</p> Signup and view all the answers

    Which Computer Vision feature can you use to generate automatic captions for digital photographs?

    <p>Describe the images</p> Signup and view all the answers

    Which service should you use to extract text, key/value pairs, and table data automatically from scanned documents?

    <p>Form Recognizer</p> Signup and view all the answers

    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?

    <p>Key phrase extraction</p> Signup and view all the answers

    In which two scenarios can you use speech recognition?

    <p>Providing closed captions for recorded or live videos</p> Signup and view all the answers

    You need to build an app that will read recipe instructions aloud to support users who have reduced vision. Which service should you use?

    <p>Speech</p> Signup and view all the answers

    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?

    <p>Natural language processing</p> 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?

    <p>QnA Maker</p> Signup and view all the answers

    In which two scenarios can you use a speech synthesis solution?

    <p>An AI character in a computer game that speaks audibly to a player</p> Signup and view all the answers

    You are building a knowledge base by using QnA Maker. Which file format can you use to populate the knowledge base?

    <p>PDF</p> Signup and view all the answers

    In which scenario should you use key phrase extraction?

    <p>Identifying which documents provide information about the same topics</p> Signup and view all the answers

    Which type of machine learning should you use to identify groups of people who have similar purchasing habits?

    <p>Clustering</p> Signup and view all the answers

    Which metric can you use to evaluate a classification model?

    <p>True positive rate</p> Signup and view all the answers

    Which two components can you drag onto a canvas in Azure Machine Learning designer?

    <p>Dataset</p> Signup and view all the answers

    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?

    <p>Split Data</p> Signup and view all the answers

    You have the Predicted vs. True chart shown. Which type of model is the chart used to evaluate?

    <p>Regression</p> Signup and view all the answers

    Which type of machine learning should you use to predict the number of gift cards that will be sold next month?

    <p>Regression</p> Signup and view all the answers

    You have a dataset on taxi journeys. What should you use as a feature to predict the fare of a taxi journey?

    <p>The trip distance of individual taxi journeys</p> Signup and view all the answers

    You need to predict the sea level for the next 10 years. Which type of machine learning should you use?

    <p>Regression</p> Signup and view all the answers

    Which service should you use to extract text, key/value pairs, and table data from scanned documents?

    <p>Form Recognizer</p> Signup and view all the answers

    You are publishing an inference pipeline in Azure ML designer. Which parameters should you use to access the web service?

    <p>The REST endpoint</p> Signup and view all the answers

    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?

    <p>Classification</p> Signup and view all the answers

    What tasks require an enterprise workspace in Azure Machine Learning?

    <p>Use a graphical user interface (GUI) to run automated machine learning experiments</p> Signup and view all the answers

    Which fields should be used as features to predict the income range of a customer?

    <p>Age</p> Signup and view all the answers

    For processing retail store images and identifying competitor products using a custom model, which Azure Cognitive Services should be used?

    <p>Custom Vision</p> Signup and view all the answers

    Which metrics can be used to evaluate a regression model?

    <p>Root mean squared error (RMSE)</p> Signup and view all the answers

    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?

    <p>A reduced workload for the customer service agents</p> Signup and view all the answers

    For a machine learning project, how should you split data for training and evaluation?

    <p>Randomly split the data into rows for training and rows for evaluation</p> Signup and view all the answers

    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?

    <p>Enable Explain best model</p> Signup and view all the answers

    Inclusiveness, as a Microsoft guiding principle for responsible AI, focuses on empowering everyone, including people with impairments. What does this principle emphasize?

    <p>Inclusiveness</p> Signup and view all the answers

    When building an AI system to meet the Microsoft transparency principle for responsible AI, which task should be included?

    <p>Ensure the training dataset is representative of the population</p> Signup and view all the answers

    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?

    <p>Natural Language Processing</p> Signup and view all the answers

    Which AI service can you use to interpret the meaning of a user input such as Call me back later?

    <p>Language Understanding (LUIS)</p> Signup and view all the answers

    You are developing a chatbot solution in Azure. Which service should you use to determine a user's intent?

    <p>Language Understanding (LUIS)</p> Signup and view all the answers

    You need to make the written press releases of your company available in a range of languages. Which service should you use?

    <p>Translator</p> Signup and view all the answers

    Which two languages can you use to write custom code for Azure Machine Learning designer?

    <p>R</p> Signup and view all the answers

    Your company wants to build a recycling machine for bottles. Which type of AI workload should the company use?

    <p>Computer vision</p> Signup and view all the answers

    In which two scenarios can you use the Form Recognizer service?

    <p>Identify the retailer from a receipt</p> Signup and view all the answers

    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?

    <p>Optical character recognition (OCR)</p> Signup and view all the answers

    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?

    <p>Optical character recognition (OCR)</p> Signup and view all the answers

    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?

    <p>Object detection</p> Signup and view all the answers

    Match the types of computer vision workloads to the appropriate scenarios.

    <p>Facial Recognition = Face detection, person identification, perceived emotion recognition, recognition and grouping of similar faces in images OCR = Object Detection = Object detection similar to tagging, returns bounding box coordinates for each object found</p> Signup and view all the answers

    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?

    <p>Object Detection</p> Signup and view all the answers

    To complete the sentence, select the appropriate option in the answer area.

    Signup and view all the answers

    You send an image to a Computer Vision API and receive back the annotated image shown. Which type of computer vision was used?

    <p>Object Detection</p> Signup and view all the answers

    What are two tasks that can be performed by using the Computer Vision service?

    <p>Detect faces in an image</p> Signup and view all the answers

    What is a use case for classification?

    <p>Predicting whether someone uses a bicycle to travel to work based on the distance from home to work</p> Signup and view all the answers

    What are two tasks that can be performed by using computer vision?

    <p>Detect the color scheme in an image</p> Signup and view all the answers

    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?

    <p>Face</p> Signup and view all the answers

    In which two scenarios can you use the Form Recognizer service?

    <p>Extract the invoice number from an invoice</p> Signup and view all the answers

    Match the facial recognition tasks to the appropriate questions.

    <p>Verification = Identity verification Similarity = Finding similar faces based on a target face</p> Signup and view all the answers

    Which Computer Vision feature can you use to generate automatic captions for digital photographs?

    <p>Describe the images</p> Signup and view all the answers

    Which service should you use to extract text, key/value pairs, and table data automatically from scanned documents?

    <p>Form Recognizer</p> Signup and view all the answers

    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?

    <p>key phrase extraction</p> Signup and view all the answers

    In which two scenarios can you use speech recognition?

    <p>creating a transcript of a telephone call or meeting</p> Signup and view all the answers

    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?

    <p>Speech</p> Signup and view all the answers

    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?

    <p>natural language processing</p> 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?

    <p>QnA Maker</p> Signup and view all the answers

    In which two scenarios can you use a speech synthesis solution?

    <p>an automated voice that reads back a credit card number entered into a telephone by using a numeric keypad</p> Signup and view all the answers

    You are building a knowledge base by using QnA Maker. Which file format can you use to populate the knowledge base?

    <p>PDF</p> Signup and view all the answers

    In which scenario should you use key phrase extraction?

    <p>identifying which documents provide information about the same topics</p> Signup and view all the answers

    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?

    <p>Inclusiveness</p> Signup and view all the answers

    What are three Microsoft guiding principles for responsible AI?

    <p>Fairness</p> Signup and view all the answers

    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?

    <p>The Detect operation in the Face service</p> Signup and view all the answers

    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?

    <p>Transparency</p> Signup and view all the answers

    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?

    <p>Establish a risk governance committee that includes members of the legal team, members of the risk management team, and a privacy officer</p> Signup and view all the answers

    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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