In this post I briefly explain about new Teams calling API (currently, in beta) with Microsoft Graph for your beginning.
Azure Machine Learning : Walkthrough of Key Features
In this post, I’ll show you how Azure ML helps your ML/AI workloads with overall features and code examples.
First look at Azure Dev Spaces – Collaborate in shared AKS cluster
With Azure Dev Spaces, you can build and debug microservices in Kubernetes cluster without installing entire system in your local desktop.
In this post I introduce Azure Dev Spaces using command line, and see how it works.
Speed up Inference by TensorRT (Step-by-Step on Azure)
In this post, I’ll show you how to optimize models in TensorFlow by using TensorRT for ONNX on Microsoft Azure.
Run FPGA Accelerated Serving (“Project Brainwave”)
Azure Machine Learning Hardware Accelerated Models (Project Brainwave) provides hardware accelerated machine learning with FPGA.
In Github tutorial, there are several useful helper classes and functions (with python) which encapsulate boilerplate code to achieve provisioning steps. In this post I show you the same steps without these helpers. With these steps I hope it helps you to understand new FPGA-enabled services and how it’s working.
Azure Databricks tutorial for TensorFlow developers (TensorFlowOnSpark)
Here I show you TensorFlowOnSpark on Azure Databricks. With this tutorial, you can learn how to use Azure Databricks through lifecycle, such as – cluster management, analytics by notebook, working with external libraries, working with surrounding Azure services, submitting a job for production, etc.
Run deep learning workloads on SQL Server Machine Learning Services (rxNeuralNet)
In this post, we quick view how to run the workloads with neural networks (deep learning workloads) in SQL Server.
SQL Server Machine Learning Services – 3 Ways to Run ML Workloads
In this post I show you several approaches for using SQL Server in-database machine learning workloads (R / Python workloads) with pros and cons.
Run Spark jobs on Azure Batch – Azure AZTK
By using aztk, you can easily deploy and drop your Spark cluster in the cloud (Azure) and you can take agility for parallel programming (for ex, starting with low-capacity VMs, performance testing with large size or GPU accelerated, etc) with massive cloud computing power.
Here I show you our machine learning tutorials (PySpark and MLlib) with aztk.
How to use custom scopes for admin consent in Entra ID
In this post I show you the tips for using admin consent for the scopes of Outlook REST API, 3rd party apps, or your own custom apps in Azure AD v2 endpoint. (Using UI, you can set the scopes only for Microsoft Graph.)
tsmatz