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…

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,…

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,…

Deploy a machine learning model with the designer

Create a real-time inference pipeline To deploy your pipeline, you must first convert the training pipeline into a real-time inference pipeline. This process removes training modules and adds web service inputs and outputs to handle requests. Create a real-time inference pipeline Above the pipeline canvas, select Create inference pipeline > Real-time inference pipeline.Your pipeline should now look like…

What is Azure Machine Learning?

Azure Machine Learning can be used for any kind of machine learning, from classical ml to deep learning, supervised, and unsupervised learning. Whether you prefer to write Python or R code or zero-code/low-code options. Start training on your local machine and then scale out to the cloud. The service also interoperates with popular open-source tools,…

MLOps: Model management, deployment and monitoring with Azure Machine Learning

learn how to use Azure Machine Learning to manage the lifecycle of your models. Azure Machine Learning uses a Machine Learning Operations (MLOps) approach. MLOps improves the quality and consistency of your machine learning solutions. Azure Machine Learning provides the following MLOps capabilities: Create reproducible ML pipelines. Pipelines allow you to define repeatable and reusable…

Azure Platform for Data Engineers(part-2)

Explore data types: Azure provides many data platform technologies to meet the needs of common data varieties. It’s worth reminding ourselves of the two broad types of data: structured data and nonstructured data. Structured data In relational database systems like Microsoft SQL Server, Azure SQL Database, and Azure SQL Data Warehouse, data structure is defined…