Azure AI Fundamentals: Machine Learning with Azure Services

Azure 2020    |    Beginner
  • 18 Videos | 1h 58m 41s
  • Includes Assessment
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Azure ML provides a suite of services to help with machine learning by providing a single interface to build, manage, deploy, test, and collaborate via the Azure Machine Learning Studio. In this course, you'll learn about the Azure ML services provided, including as Machine Learning designer and automated machine learning. You'll explore how to access and use the Azure Machine Learning Studio and review the Machine Learning features available in the service. In particular, you'll learn about the features of the Computer Vision, Custom Vision, Face, and Form Recognizer services. This course is one of a collection that prepares learners for the Microsoft Azure AI Fundamentals (AI-900) exam.

WHAT YOU WILL LEARN

  • discover the key concepts covered in this course
    describe the machine learning services provided by Azure
    describe the Azure Machine Learning Studio
    register and signup for an Azure Machine Learning Studio account and access the studio dashboard
    inspect the Azure ML Studio sidebar components used for creating machine learning workflows
    describe the features and services provided by the Azure Computer Vision Service
    describe the uses of the Custom Vision Service
    describe the features and services provided by the Azure Face service
    describe the features and capabilities of the Form Recognizer service
  • identify the process and functions of Azure ML Studio for creating, running, and maintaining AI workloads
    identify and describe the features of a compute target
    describe a dataset and how they are created and managed
    manage pipelines in the Azure ML Studio interface
    describe the limitations and features of automated ML model training
    describe an experiment and how to run it in Azure ML studio
    identify and interpret the evaluation metrics for a run of a Classification model
    identify and interpret the evaluation metrics for a run of a Regression model
    summarize the key concepts covered in this course

IN THIS COURSE

  • Playable
    1. 
    Course Overview
    1m 19s
    UP NEXT
  • Playable
    2. 
    Machine Learning Services Provided by Azure
    8m 22s
  • Locked
    3. 
    Azure Machine Learning Studio
    7m 3s
  • Locked
    4. 
    Signing up for an Azure ML Studio Account
    4m 37s
  • Locked
    5. 
    Inspecting the Azure Machine Learning Features
    8m 47s
  • Locked
    6. 
    Features of the Computer Vision Service
    5m 34s
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    7. 
    Features of the Custom Vision Service
    5m 34s
  • Locked
    8. 
    Features of the Face Service
    6m 26s
  • Locked
    9. 
    Features of the Form Recognizer Service
    5m 30s
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    10. 
    Identifying Azure ML Workloads
    6m 19s
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    11. 
    Compute Resources
    6m 5s
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    12. 
    Creating and Managing Datasets in Azure ML Studio
    6m 30s
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    13. 
    Managing Pipelines in Azure ML Studio
    6m 28s
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    14. 
    Algorithms Used for Model Training
    7m 28s
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    15. 
    Azure ML Services Experiments
    8m 49s
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    16. 
    Interpreting Evaluation Metrics for Classification
    7m 14s
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    17. 
    Interpreting Model Evaluation Metrics for Regression