Azure Machine Learning Platform Quiz
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Questions and Answers

What is the primary focus of a data scientist working with Azure Machine Learning?

  • Training and deploying machine learning models (correct)
  • Developing mobile applications
  • Managing cloud infrastructure
  • Creating Azure virtual machines
  • What is the purpose of creating an Azure Machine Learning workspace resource?

  • To manage data, compute resources, models, and endpoints related to machine learning workloads (correct)
  • To develop web applications
  • To create virtual networks in Azure
  • To set up email services
  • Why is it recommended to use version 2 (v2) of Azure Machine Learning?

  • To focus on big data processing
  • To develop new programming languages
  • To work with older machine learning algorithms
  • To introduce consistency of features and terminology across interfaces (correct)
  • What are the key resources and assets that can be managed in an Azure Machine Learning workspace?

    <p>Data, compute resources, models, and endpoints</p> Signup and view all the answers

    Which platform provides a comprehensive set of resources and assets to train and deploy effective machine learning models?

    <p>Azure Machine Learning on Microsoft Azure platform</p> Signup and view all the answers

    What is the primary focus of a data scientist working with Azure Machine Learning?

    <p>Training and deploying machine learning models</p> Signup and view all the answers

    What does Azure Machine Learning provide to data scientists?

    <p>A platform to train and deploy machine learning models</p> Signup and view all the answers

    What is the purpose of creating an Azure Machine Learning workspace resource?

    <p>To manage data and compute resources</p> Signup and view all the answers

    Why is it recommended to use version 2 (v2) of Azure Machine Learning?

    <p>It introduces consistency of features and terminology across interfaces</p> Signup and view all the answers

    What are the key resources and assets that can be managed in an Azure Machine Learning workspace?

    <p>Managing data, compute resources, models, endpoints, and other artifacts related to machine learning workloads</p> Signup and view all the answers

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