Sibeesh Venu's contributions

In this article, you will learn how to show recent blog posts in GitHub ReadMe using an Azure Function.

In this article, you will learn about azure cdn with azure web app - access to font at cdn has been blocked by cors policy.

In this article, you will cover steps to transfer repositories, ensuring smooth transition of version-controlled projects while maintaining integrity and collaboration across teams.

Transfer Azure DevOps work items between organizations effortlessly using migration tools. Export data from source organization, import to target organization, ensuring seamless transition of Agile projects across teams.

In this article you will see how i find time to write blogs and for my hobbies.

The Microsoft Azure has a lot to offer when it comes to Cognitive Services, trying them out is really fun. Here in this article, we are going to see how we can detect and read texts from an image and show it in the display using the Cognitive Service Computer Vision AI.

July 1st, 2019 was one of my favorite days of the year. Guess what? I am a Microsoft MVP for the fourth time in a row. Yes, you heard me right.

In this article, we will see how we can publish one of our GitHub repositories as a GitHub page and problems associated with it.

Learn how to migrate an on-premises Virtual Machine to Azure using VHD files. Convert VHDX to VHD, upload to Azure Blob storage, create a Managed Image, and deploy an Azure VM using PowerShell commands. Ensure compatibility and follow best practices for seamless cloud migration.

In this article, we will create our own cryptocurrency and our own private consortium network in Azure. We will be using Ethereum proof-of-work consortium solution from Azure.

In this article, we will see how to set up our MXChip and get all the information, such as - Temperature, Humidity, Pressure etc. received to our Azure IoT Hub.

Here, in this article, we will see how we can show the real-time data from our IoT device in an Angular application using Azure SignalR service and Azure Functions.

Here in this article, we will send some data to our Azure IoT hub and we will connect an Azure Function with our IoT Hub using IoTHubTrigger Event Hub Trigger Attribute.

In this article, we are going to see how we can set up an Azure Function as an Output job topology of an Azure Stream Analytics job. Doesn’t that sound interesting?

Creating Azure Stream Analytics jobs and working with them is always fun. And what if there were a tool which helps you create a stream solution in Visual Studio so that you don’t have to go over to the browser and do some manual button clicks? That’s where the Azure Data Lake and Stream Analytics Tool extension comes into play.

The capability of an Azure Stream Analytics Job is huge, and here in this post we are going to discuss this.

I am using the Operating System Windows 1o in my machine, and I will not be able to open the Linux based files in Windows 10 as it cannot identify those file types. Hm, it is expected, and nothing wrong it. But we have a workaround to do that. Here in this article, I will explain the steps you should be followed. Let’s skip the introduction and start doing some amazing things. Let’s just start then.

Here in this article, we are going to use the Microsoft Custom Vision AI, which is a cognitive AI service. The Custom Vision service uses the machine learning to classify the images we are uploading. The only thing we are required to do is, just specifying the correct tag for each image, you can also tag thousands of images at a time. The AI algorithm is super powerful to give us better accuracy and once the model is trained, use the same to classify new images according to the needs of your app.

Let’s try something different this time, here in this article you will learn how you can set up your Raspberry PI with the Microsoft Windows 10 IoT core.

There are many cases, where a Raspberry Pi can do the things you want perfectly, in this post we are not going to cover those, instead, we will be going through how we can set up your Raspberry Pi. Let’s just start then.