Azure Machine Learning

A workspace is a context for the experiments, data, compute targets, and other assets associated with a machine learning workload. Workspaces for Machine Learning Assets A workspace defines the boundary for a set of related machine learning assets. You can use workspaces to group machine learning assets based on projects, deployment environments (for example, test…

Azure SQL Database to store App data

Managing data is a critical component of any business. Relational databases, and specifically Microsoft SQL Server, have been among the most common tools for handling that data for decades. If we want to manage our data using the cloud, we can just use Azure virtual machines to host our own Microsoft SQL Server instances. Sometimes that’s the…

Understand The Service Azure Provides for Data Engineers

Even the most experienced data engineer can feel overwhelmed by the range of data platform technologies in Microsoft Azure. In diverse scenarios and industries, data engineers must solve complex data problems to provide business value through data. By understanding the data types and capabilities of the data platform technologies, a data engineer can pick the…

Device Security for cloud iot device

Security is a critical concern when deploying and managing IoT devices. Cloud IoT Core offers the following security features: Per-device public/private key authentication using JSON Web Tokens (JWTs, RFC 7519). This limits the surface area of an attack, because a compromised key would affect only a single device and not the whole fleet. JWTs are valid…

Create your first Cloud Pub/Sub topic

A Cloud Pub/Sub topic is a named resource to which devices send messages. Create your first topic with the following command: gcloud pubsub topics create my-topic You will send several messages to this topic later. Create a subscription to the device’s topic Run the following command to create a subscription, which allows you to view the messages…

Predict prices using regression with ML.NET

You can follow along or download the source code here. Create a console application Create a .NET Core Console Application called “TaxiFarePrediction”. Create a directory named Data in your project to store the data set and model files. Install the Microsoft.ML NuGet Package:In Solution Explorer, right-click the project and select Manage NuGet Packages. Choose “nuget.org” as the Package source, select the Browse tab, search for Microsoft.ML,…

Create an IoT hub using the Azure portal

Create an IoT hub This section describes how to create an IoT hub using the Azure portal. Sign in to the Azure portal. From the Azure homepage, select the + Create a resource button, and then enter IoT Hub in the Search the Marketplace field. Select IoT Hub from the search results, and then select Create. On the Basics tab, complete the fields as follows: Subscription: Select the…

Deploy and run an IoT device simulation in Azure

Deploy Device Simulation When you deploy Device Simulation to your Azure subscription, you must set some configuration options. Sign in to azureiotsolutions.com using your Azure account credentials. Click the Device Simulation tile: Click Try now on the Device Simulation description page: On the Create Device Simulation solution page, enter a unique Solution name. Select the Subscription and Region you want to use to deploy the solution accelerator. Typically,…

How Azure Machine Learning works: Architecture and concepts

How Azure Machine Learning works: Architecture and concepts Register for Upcoming event and send us a mail: Workflow The machine learning model workflow generally follows this sequence: Train Develop machine learning training scripts in Python or with the visual designer. Create and configure a compute target. Submit the scripts to the configured compute target to run in that environment….

Introduction Into Azure Machine Learning

Azure Machine Learning is a platform for operating machine learning workloads in the cloud. Built on the Microsoft Azure cloud platform, Azure Machine Learning enables you to manage: Scalable on-demand compute for machine learning workloads. Data storage and connectivity to ingest data from a wide range sources. Machine learning workflow orchestration to automate model training,…