A Simple Introduction to Computer Vision
Computer Vision is a field of AI that renders machines the power to emulate human vision to perceive the world visually by processing images, either from a live camera feed or from digital photographs or videos. Some exciting examples of computer vision in practice today are: autonomous vehicles, google translate app, facial recognition, healthcare, real-time sports tracking, agriculture, and manufacturing.
There are numerous types of computer vision problems that data scientists and AI engineers can solve with the help of a mix of custom machine learning models and platform-as-a-service (PaaS) solutions. Microsoft Azure offers you numerous cognitive services that have prebuilt computer vision model capabilities.
Learn AI Computer Vision with Azure
Microsoft AI School hosts an impressive list of modules to help you get started with Computer Vision in Azure. To conquer Computer Vision in Azure, you may follow the following learning path featured in Microsoft’s AI School - “Explore computer vision in Microsoft Azure.” This learning path has six modules. Read ahead to get a quick peek at each module of this learning path.
Prerequisite: You must be able to navigate the Azure portal to pursue this learning path.
Module1: Analyze Images with The Computer Vision Service
Computer Vision is a cognitive service in Microsoft Azure that analyzes content in images and videos and returns detailed information about an image and the objects depicted by the image.
In the first module, you will learn how to use the computer vision service in Azure to analyze images. The primary objectives of this module are to help you:
- Identify image analysis tasks that can be performed with Azure’s Computer Vision service.
- Provision a Computer Vision resource.
- Use a Computer Vision resource to analyze an image.
Here’s an overview of the units covered within this module:
Module 2: Classify Images with The Custom Vision service
Image classification is the field of Artificial Intelligence that harnesses the predictive capabilities of a machine learning model to enable AI systems to detect objects or real-world items within an image based on their unique properties. Some potential use cases of image classification are: product identification, disaster investigation, medical diagnosis, and anomaly detection. Microsoft Azure’s Custom Vision is a cognitive service in Azure that encapsulates common techniques to train and publish image classification models as a software service. This allows you to deploy classification models with minimal knowledge of deep learning techniques.
Thus, this module will help you learn how to use the Computer Vision service in Azure to create an image classification model. The primary objectives of this module are to help you:
- Identify image classification scenarios and technologies.
- Provision a Custom Vision resource and use the Custom Vision portal.
- Train an image classification model.
- Publish and consume an image classification model.
Here’s an overview of the units covered within this module:

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