Microsoft Azure Cognitive Services Crash Course

After watching this clip, you will have a good understanding of the topics we will cover in this section.

In this demo, we will create a new Azure Cognitive Services resource in the Azure Portal. This resource will be used in most demos in the rest of this course.

In this lecture, we will talk about the Computer Vision API capabilities and APIs.

In this lecture, we will work with the Computer Vision API in action. Various APIs will be tested in Postman.

The attached Postman collection includes requests for ALL demos in this section.

In this lecture, we will learn about the Face API and its capabilities.

In this demo, we will see the Face API in action. Postman is used to call these REST APIs.

In this clip, we will learn when to use the Custom Vision API.

In this demo, we will use the Custom Vision portal to create a custom image classifier.

In this lecture, we will learn all about three Vision services:

1. Video Indexer

2. Form Recognizer

3. Ink Recognizer

In this demo, we will see the Video Indexer service in action.

In this lecture, we will work with the Form Recognizer service.

In this lecture, we will learn about the Ink Recognizer service. This service allows you to capture and process digital ink input (Stylus, touch and mouse strokes)

Congratulations! Now you have a solid understanding of Azure Cognitive Services Vision APIs. Keep up the great work.

If you like the course, please support it by reviewing and rating it. This makes a bug difference and will encourage me to create more quality content for this platform.

Thanks again and keep on learning!

Reza

In this introductory clip, we will go over the topics to discuss in this section.

In this clip we will learn all about the Speech to Text service.

In this demo, we will use the speech-to-text service to transcript a voice file into text.

The attached Postman collection includes requests for ALL demos in this section.

In this clip, we will go over the capabilities of the text-to-speech service.

In this demo, we will use the text-to-speech service to create a human-sounding voice from text.

In this clip, we will learn about the Speech Translation service capabilities.

In this demo, we will use the Speech Translation service to translate my recorded voice.

In this lecture, we will go over the Speaker Recognition API and its use cases.

In this clip, we will see a high-level demo of the Speaker Recognition service. The Microsoft's live demo page is used.

In this introductory clip, we will have an overview of the topics to cover in this section.

In this clip we will go over the capabilities of the Text Analytics service.

In this demo, we will use the Text Analytics service to extract meaning from some text.

The attached Postman collection includes requests for ALL demos in this section.

In this clip, we will go over the Translator Text service and its use cases.

In this clip, we will see the Translator Text API in action.

In this demo, we will create a Custom Translator by training a custom model.

In this demo, we will use the Custom Translator which we created in the previous clip.

In this clip, we will go over the QnA Maker service.

In this clip, we will create a QnA Maker knowledge base.

In this clip, we will learn about the Language Understanding (LUIS) service.

In this lecture, we will create a LUIS model for a pizza delivery shop.

In this clip, we will use the LUIS model we created in the previous demo.

In this clip, we will go over the Immersive Reader service.

In this demo, we will create an Immersive Reader instance and configure the permissions using Azure Active Directory.

In this demo, we will improve our website accessibility using the Immersive Reader service we created in the previous module.

In this clip, we will go over the topics we are covering in this section.

In this clip, we will go over the use cases of the Content Moderator service.

In this demo, we will use the Content Moderator service to extract some PIIs from text and image.

The attached Postman collection includes requests for ALL demos in this section.

In this clip, we will go over the Anomaly Detector service and will review a few use cases.

In this demo, we will use the Anomaly Detector service to detect anomalies in both Stream and Batch modes.

In this lecture, we will go over the Personalizer service and its use cases.

In this clip, we will create and configure a Personalizer instance in Azure.

In this demo, we will use the Personalizer instance in the previous demo in a C# application.

In this clip, we will go over the services to cover in this section.

In this clip, we will go over all the services under the Web Search gategory.

In this demo, we will provision a new Bing Search resource in the Azure Portal.

The attached Postman collection includes requests for ALL demos in this section.

In this demo, we will try the following services:

1. Azure Bing Web Search

2. Azure Bing Image Search

3. Azure Bing Autosuggest

4. Azure Bing Spell Check

Congratulations! You did it! Know you have a solid understanding of Azure Cognitive Services and its use cases.

In this demo, we will see how Azure Machine Learning can be used to solve AI problems not covered by Azure Cognitive Services. For this demo, we will use Azure Machine Learning to predict arrival flight delays and deploy this trained model to a RESTful API. This demo is valuable if you are planing to take Azure exam AI-100

In this demo, we will deploy our trained model to a RESTful API and use Postman to test it. This demo is valuable if you are planing to take Azure exam AI-100

Azure Cognitive Services can be used in many AL cases. If your case can't be addressed with Azure Cognitive Services, check out Azure Machine Learning.

Lets talk about exam AI-100. A great way to validate your Azure AI knowledge.

Thanks for trusting me to be your instructor for this course. I hope I've delivered on my promises.  I tried to make this course as useful and easy to follow as possible.

If you liked the course, please comment and rate it. This is important for me and will entourage me to create even more useful content.

Please reach out to my LinkedIn and Twitter with your success stories.

Thank you!

Reza Salehi