This video tutorial will walk you through the entire list of commands which are required to create an instance of Azure Cognitive Services using PowerShell.
Using PowerShell To Create Instance of Azure Cognitive Services
Getting Started With Face API Azure Cognitive Services
This video guides you through all the steps required to get started with Azure Face API including documentation links. It also demonstrates how to make a call to Face API using both client-side SDK and REST APIs.
Generate Image Thumbnail Using Azure Computer Vision and Logic Apps
This video tutorial walks you through the complete end-to-end flow on how one can generate a thumbnail from an image using Azure Cognitive Services - Computer Vision API. The workflow starts by adding an image into Azure Storage, passing it to Computer Vision, and storing the generated thumbnail back to Azure Storage and all this is achieved without writing even a single line of code.
On the technology front, it uses Azure Computer Vision API, Azure Blob Container, and Logic Apps.
Performing Sentiment Analysis Video
This video talks about an end-to-end flow, wherein an email content having a specific subject line will be read, the email body would be analyzed using Azure Cognitive Services (Sentiment analysis), analysis results would be saved in Azure Table Storage and finally, the chart would be drawn in Excel. All these steps include no coding at all.
Getting Started With Reading Text From an Image Using Azure Cognitive Services
In this article, we will learn about how we can read or extract text from an image, irrespective of whether it is handwritten or printed.
In order to read the text, two things come into the picture. The first one is Computer Vision and the second one is NLP, which is short for Natural Language Processing. Computer vision helps us to read the text and then NLP is used to make sense of that identified text. In this article, I’ll talk specifically about the text extraction part.
Extract Text From Sales Receipt Using Pre-Built Model: Azure Form Recognizer
Nowadays, where almost everything is turning to online and virtual modes, a very common problem any organization is facing is the processing of receipts that were scanned and submitted electronically for reimbursement purposes.
Now for any claim or reimbursements to get clear, first those must reach to proper accounts department based on the organization and the sector, and one way to perform this activity is by manual intervention. A person or a team must go through all those digitally scanned receipts manually and filter them based on the departments or any other validation and eligibility criteria they may have.