Exploring Microsoft Azure Cognitive Services Overview
Discover the categories and use cases of Azure's Cognitive Services, including vision, speech, and language APIs for AI-enabled applications.
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What are Microsoft Azure AI Cognitive Services
Added on 01/29/2025
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Speaker 1: Hello. In this video, I'm going to talk about Microsoft Azure Cognitive Services. There are multiple types of cognitive services which are provided by Microsoft Azure. Now, there are big categories, broad categories where these services are classified. The first one is vision. In these kinds of services, they talk about computer vision, object detection, face API recognition, action detection. So, all of these related to the vision component is what comprises of the vision cognitive services. The next type of categories are speech recognition, speech cognitive services. In this, you talk about the speech to text, text-to-speech, and other kinds of speech services. The next is language. In this, you talk about natural language processing. You talk about various different types of language classifiers. Text-to-speech is a speech service, but language classifier, you talk about language understanding, which is LUIS, language understanding integration service. Then, you have knowledge, which is QnA Maker, and you also have search, which is this Bing search services. You can do Bing geographical search services, textual services, image search services as well. Now, in all, all of these services combine together to provide artificial intelligence and machine learning use cases. Now, think about this. What are the kind of use cases you can solve with these cognitive services? With the vision APIs, you can do a facial recognition or object detection kind of a use case. Think of an assembly line in a manufacturing firm. Using the object detection at stage 3 or 4 out of 7 stages, suppose an assembly line is of 7 stages, at 3 or 4, or 3 or 4 or 2, if you are able to recognize that the part which is being manufactured is not up to the standards, and you don't want to be considering it because it's a defect. Now, you can eliminate that part in the next level, maybe 3, and saving the cost for the processing in the further stages. An example of facial recognition service can be for employees. You can enable facial recognition for login, logout, or even granting access, authorization access to a data center, finding out who came in, even for the visitors, or in conferences when visitors are visiting your booth, you can think of understanding the kind of visitor and the emotions. There are a lot of attributes you can derive to face APIs. Obviously, you can use them. Another use case is the use case of textual identification or text is that the language language translator. In travel, when you are traveling to countries where you don't have the right language, it's not English, for example, French, or Portuguese, or Spanish, you can use the language translator as a service in order to convert the text. So, there are a lot of various APIs which are available. And again, Microsoft Azure provides these APIs through endpoints. So, using these endpoints, you can call those services and enable in your application. In today's world, I want to say that a lot of organizations are focusing towards getting their apps, existing applications, AI enabled. So, you can embed these API services in your existing applications. To know more, keep watching our Microsoft Azure Cognitive Services series. In the next video, I'm going to talk about how you can use face API service. A bit technical, but you can definitely take a look. Thank you.

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