AI-900: Microsoft Azure AI Fundamentals Certification Video Training Course

AI-900: Microsoft Azure AI Fundamentals certification video training course by prepaway along with practice test questions and answers, study guide and exam dumps provides the ultimate training package to help you pass.

Describe features of computer vision workloads on Azure

1. Section Introduction

Welcome to this section. In this section, we are going to look at the Computer Vision API. The Computer Vision API now includes a plethora of features. The main focus that we are going to be looking at is the submission of images to the Computer Vision API and seeing what information this API can get back to us. So, for example, we can go ahead and submit an image to the service. It can actually go ahead and process the image. It can go ahead and tell us what objects are present in the image. So don't worry; we'll actually go through the service in this particular section. Now, when going through these services, when it comes to computer vision, when it comes to the cognitive suite of services, we are going to be using, in some cases, a Net program. Now, for the exam, you don't need to have any sort of development experience; you just need to showcase what the service can do. I want to show you examples of Net in Visual Studio 2019.

And again, it's going to be pretty simple. I'm not going to go ahead and create complicated programmes in the Net language. At the same time, I'm going to go ahead and also show you a very simple way to invoke these services, to invoke the Computer Vision service, and to invoke other services. In Azure, we're going to be using the Postman tool. So you don't need to have any development experience for that. I'll show you very clearly how you can actually go ahead and use these different services in Azure Cognitive Services. So we are going to look at the Computer Vision API. We will look at another interesting API that's known as the Face API. We will also look at the Customer Vision API. and also look at the Form Recognizer API. So all of these are the AzureCongress services that are available in Zah.

2. Azure Cognitive Services

Hi, welcome back. Now, when it comes to using the AI-based solutions that are available on Azure, we are going to be looking at Azure Cognitive Services. So there are a lot of services that we're going to go ahead and cover as part of this course. So some of the important services that we are going to add to COVID are, firstly, when it comes to the Vision API, so we are going to look at the Computer Vision API. We're going to be looking at custom vision. We're going to be looking at the Face API and the form recognizer. Aside from this, we also have the Speech API in place. So, if you want to convert speech to text, or if you want to do speech translation, all of this is available as part of this suite of services or APIs that are available as part of your cognitive services. So there are a lot of services that are available, and we're going to go in and cover the important ones, which are basically important from an exam perspective. So let's go ahead.

3. Introduction to Azure Computer Vision solutions

Hi, and welcome back. Now, in this chapter, I want to go through the different types of computer vision solutions that are available in Azure as part of Azure Cognitive Services. So first, we have the ability to go ahead and classify images. So we have something known as image classification. So over here, this involves analysing an image and identifying a class that the image falls under. So, for example, if you have a picture of a cat, as shown over here, So we, as human beings, know that this is a picture of a cat. But how does a computer know that when we submit this image, it is, in fact, a cat? So normally, you would need to go ahead and create machine learning models, train that model to go ahead and understand images of cats, and then go ahead and give us the solution or the answer that when we submit an image, this is indeed a cat.

However, when it comes to Azure and computer vision solutions, these machine learning models with image classification capabilities are already in place. They've already been trained. So we can actually go ahead and submit images to the computer vision service and have the ability to go out and classify images. It can also go ahead and do object detection as well. So over here, it has the ability to also go out and identify the different objects within the image itself. So, for example, you can go ahead and identify that there is a cat; it can identify that there are flowers. You can also get boundaries for the object itself. So, for example, this is very important when it comes to driving. So, when it comes to detecting cars on the road, it's important to go ahead and identify the car as an object and what the car's position is at that point in time if you want to go ahead and see the distance between cars.

So you can also go ahead and get the boundaries of the object as well. Apart from that, you also have optical character recognition. So over here, if you go ahead and submit an image that has text in it, it has the ability to go ahead and scan the text from the image itself. It has another popular service known as facial recognition. So over here, you can get different aspects of the face itself. So you can tell whether the person is male or female over here. Just from the picture itself, you can get an idea of the person's estimated age. You'll be able to recognise a person as well. So again, these are all different features. when it comes to the computer vision solutions that are available in Azure.

4. A look at the Computer Vision service

Now, if you want to go ahead and see how, say, the Computer Vision Service works when it comes to Azure Cognitive Services, So you can go to the Azure Cognitive Services Homepage, and then scroll down to see the vision services that are available. Over here, you can actually go to the Computer Vision service. So this service is used to analyse your images and provide you with relevant data based on those images. So if you go ahead and scroll down, over here, there will be one default image in place, and over here, you're getting information about the image. Now over here, you also have the ability to go ahead and upload your own image.

So let me go ahead and do that. Let me go ahead and click on Browse and browse for an image that I have on my local machine. So I'm browsing for an image that I have on my local machine. Let me go ahead and hit Open. So now this particular service has actually gone ahead. It's taken my image, and it has also gone ahead and detected certain objects in the image. Over here, it has not gone ahead and detected all of the objects, but most of the objects have been detected via the service. Now for each of the objects that it has gone ahead and detected, it is going ahead and giving you relevant information over here about all the objects in that particular image, basically those that it has detected. So over here, you can see the object itself; it's a cup. Over here, you can see the confidence level.

So on a scale of zero to one, it's going in and giving you a confidence level based on how confident it is when it is making the decision on what the object is that it has gone ahead and detected. Now over here, you can also see bounding rectangular coordinates. So what this means is that it is going ahead and giving you coordinates about the underlying object that it has gone ahead and detected. So over here, when you're looking at, let's say, this bounding box for this particular object, it is going in and giving you the positional coordinates of the object itself, and then it also has the ability to go ahead and give you various tags. So over here, it has gone ahead and understood that, yes, there is a table. It also has a flow. So it has gone ahead and detected certain attributes about the object itself. So there's a lot of information that you can actually get via the service. You just go ahead and upload an image to the service. And over here, it's giving you these different attributes. So this is the power that you have with the computer vision service.

Now, please note that when it comes to these services in Azure, I'm going to go ahead and show you how you can call these services, for example, from an anet programme in Visual Studio 2019, or even from a tool that's a Postman tool where you can actually go ahead and call these APIs. Now, the entire reason I'm actually going ahead and showcasing these examples is because I always want students to have a good understanding of the services that are present in Azure and how you can make use of them. Have you looked over here on this page? So it's giving you a description and an example of what this service can do in your organization, in your company.

So you're not going to use a space to go ahead and basically tell me attributes about an image or an object? No, you will be developing applications or being responsible for the implementation of applications that will actually go ahead and use these services. So it's very important for you as an IT professional to go ahead and understand how you can invoke these services. And that's the extra level I actually give to my students. I want y'all to know the full power and capabilities of these services. So that's why I'm going to go ahead and give it extra when it comes to how you work with your cognitive services.

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