Azure AI Fundamentals: Computer Vision
Azure 2020
| Beginner
- 15 Videos | 1h 22m 31s
- Includes Assessment
- Earns a Badge
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
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discover the key concepts covered in this coursedescribe how computer vision works and how it can be used to solve real world problemsrecognize the features and capabilities of the Azure Computer Vision servicesidentify the different Computer Vision models available for doing image classification, object detection, and image analysisdescribe how Computer Vision identifies real world items and objectsuse the Computer Vision service to analyze imagesuse studio to describe and tag images used for training a classification modeltraining a classifier to classify items in an image
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evaluate the results of the classifier modeldeploy and test the prediction capabilities of the Modeltrain a model to detect objects in an imageevaluate the results of an object detection modeldeploy and test the model as a servicedescribe the purpose and uses of semantic segmentationsummarize the key concepts covered in this course
IN THIS COURSE
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1.Course Overview1m 23sUP NEXT
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2.Computer Vision4m 59s
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3.Azure Computer Vision Services4m 12s
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4.Computer Vision Models6m 13s
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5.Classify and Detect Objects5m 18s
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6.Analyzing Images Using Computer Vision Service10m 31s
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7.Describing and Tagging Images6m 59s
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8.Training a Classifier Model4m 30s
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9.Evaluating a Classifier Model5m 25s
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10.Testing and Using a Model for Prediction7m 17s
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11.Training an Object Detection Model7m 50s
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12.Evaluating an Object Detection Model4m 43s
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13.Using the Model as a Service7m 27s
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14.Semantic Segmentation4m 49s
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15.Course Summary54s
EARN A DIGITAL BADGE WHEN YOU COMPLETE THIS COURSE
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