Azure AI Fundamentals: Machine Learning with Azure Services

Azure    |    Beginner
  • 18 videos | 1h 50m 41s
  • Includes Assessment
  • Earns a Badge
Rating 4.3 of 42 users Rating 4.3 of 42 users (42)
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

  • 1m 19s
  • 8m 22s
    In this video, find out how to describe the machine learning services provided by Microsoft Azure. FREE ACCESS
  • Locked
    3.  Azure Machine Learning Studio
    7m 3s
    Upon completion of this video, you will be able to describe Azure Machine Learning Studio. FREE ACCESS
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    4.  Signing up for an Azure ML Studio Account
    4m 37s
    During this video, you will learn how to register and sign up for an Azure Machine Learning Studio account and access the studio dashboard. FREE ACCESS
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    5.  Inspecting the Azure Machine Learning Features
    8m 47s
    To learn how to inspect the Azure ML Studio sidebar components used for creating machine learning workflows, keep reading. FREE ACCESS
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    6.  Features of the Computer Vision Service
    5m 34s
    Learn how to describe the features and services provided by the Azure Computer Vision Service. FREE ACCESS
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    7.  Features of the Custom Vision Service
    5m 34s
    In this video, you will learn how to describe the uses of the Custom Vision Service. FREE ACCESS
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    8.  Features of the Face Service
    6m 26s
    During this video, you will learn how to describe the features and services provided by the Azure Face service. FREE ACCESS
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    9.  Features of the Form Recognizer Service
    5m 30s
    In this video, you will learn how to describe the features and capabilities of the Form Recognizer service. FREE ACCESS
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    10.  Identifying Azure ML Workloads
    6m 19s
    Discover how to identify the process and functions of Azure ML Studio for creating, running, and maintaining AI workloads. FREE ACCESS
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    11.  Compute Resources
    6m 5s
    In this video, you will identify and describe the features of a computer target. FREE ACCESS
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    12.  Creating and Managing Datasets in Azure ML Studio
    6m 30s
    After completing this video, you will be able to describe a dataset and how it is created and managed. FREE ACCESS
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    13.  Managing Pipelines in Azure ML Studio
    6m 28s
    In this video, find out how to manage pipelines in the Azure ML Studio interface. FREE ACCESS
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    14.  Algorithms Used for Model Training
    7m 28s
    Upon completion of this video, you will be able to describe the limitations and features of automated machine learning model training. FREE ACCESS
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    15.  Azure ML Services Experiments
    8m 49s
    During this video, you will learn how to describe an experiment and how to run it in Azure ML studio. FREE ACCESS
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    16.  Interpreting Evaluation Metrics for Classification
    7m 14s
    Find out how to identify and interpret the evaluation metrics for a run of a classification model. FREE ACCESS
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    17.  Interpreting Model Evaluation Metrics for Regression
    7m 41s
    Learn how to identify and interpret the evaluation metrics for a Regression model. FREE ACCESS
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    18.  Course Summary
    55s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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