Azure AI Fundamentals: Computer Vision

Azure    |    Beginner
  • 15 videos | 1h 22m 31s
  • Includes Assessment
  • Earns a Badge
Rating 4.4 of 36 users Rating 4.4 of 36 users (36)
Computer vision is the machine learning capability to allow computers to "see" similar to how a person can see, and be able to identify, distinguish, and interpret objects, people, and even text from images or video. In this course you will learn about the Azure ML Computer Vision service, Computer Vision Models, and how it can be trained and used to detect and classify objects in images and videos using a Classifier model and semantic segmentation. You'll also learn how to evaluate the results of an object detection model. 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 how computer vision works and how it can be used to solve real world problems
    Recognize the features and capabilities of the azure computer vision services
    Identify the different computer vision models available for doing image classification, object detection, and image analysis
    Describe how computer vision identifies real world items and objects
    Use the computer vision service to analyze images
    Use studio to describe and tag images used for training a classification model
    Training a classifier to classify items in an image
  • Evaluate the results of the classifier model
    Deploy and test the prediction capabilities of the model
    Train a model to detect objects in an image
    Evaluate the results of an object detection model
    Deploy and test the model as a service
    Describe the purpose and uses of semantic segmentation
    Summarize the key concepts covered in this course

IN THIS COURSE

  • 1m 23s
  • 4m 59s
    Discover how to describe how computer vision works and how it can be used to solve real world problems. FREE ACCESS
  • Locked
    3.  Azure Computer Vision Services
    4m 12s
    In this video, you will learn about the features and capabilities of the Azure Computer Vision services. FREE ACCESS
  • Locked
    4.  Computer Vision Models
    6m 13s
    After completing this video, you will be able to identify the different Computer Vision models available for doing image classification, object detection, and image analysis. FREE ACCESS
  • Locked
    5.  Classify and Detect Objects
    5m 18s
    In this video, find out how Computer Vision identifies real world items and objects. FREE ACCESS
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    6.  Analyzing Images Using Computer Vision Service
    10m 31s
    Upon completion of this video, you will be able to use the Computer Vision service to analyze images. FREE ACCESS
  • Locked
    7.  Describing and Tagging Images
    6m 59s
    During this video, you will learn how to use studio to describe and tag images used for training a classification model. FREE ACCESS
  • Locked
    8.  Training a Classifier Model
    4m 30s
    Find out how to train a classifier to classify items in an image. FREE ACCESS
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    9.  Evaluating a Classifier Model
    5m 25s
    Learn how to evaluate the results of the classifier model. FREE ACCESS
  • Locked
    10.  Testing and Using a Model for Prediction
    7m 17s
    In this video, you will learn how to deploy and test the prediction capabilities of the Model. FREE ACCESS
  • Locked
    11.  Training an Object Detection Model
    7m 50s
    During this video, you will discover how to train a model to detect objects in an image. FREE ACCESS
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    12.  Evaluating an Object Detection Model
    4m 43s
    In this video, you will learn how to evaluate the results of an object detection model. FREE ACCESS
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    13.  Using the Model as a Service
    7m 27s
    Discover how to deploy and test the model as a service. FREE ACCESS
  • Locked
    14.  Semantic Segmentation
    4m 49s
    In this video, you will discover the purpose and uses of semantic segmentation. FREE ACCESS
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    15.  Course Summary
    54s
    In this video, we will summarize the key concepts covered in this course. FREE ACCESS

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