2024年7月12日 · This article describes three Azure architectures for machine learning operations that have end-to-end continuous integration and continuous delivery (CI/CD) pipelines and retraining pipelines. The architectures are for these AI applications: Classical machine learning; Computer vision (CV) Natural language processing

2025年2月3日 · As an architect designing a solution, it's important to understand the AI and machine learning landscape and how Azure offers solutions to integration into your workload design.

2024年8月28日 · Learn about the architecture and concepts for Azure Machine Learning. This article gives you a high-level understanding of the components and how they work together to assist in the process of building, deploying, and maintaining machine learning models.

Welcome to the Azure Machine Learning examples repository! The azureml-examples repository contains examples and tutorials to help you learn how to use Azure Machine Learning (Azure ML) services and features. If you're getting started with Azure ML, consider working through our tutorials for the v2 Python SDK.

2022年6月30日 · Azure Machine Learning is an open-source friendly, machine learning platform that can be used to implement full machine learning lifecycle and MLOps through integration with GitHub (or Azure DevOps) and Responsible AI technologies which support you to develop, use and govern AI responsibly.

Below is the MLOps v2 architecture for a Classical Machine Learning scenario on tabular data using Azure Machine Learning along with explanation of the main elements and details. This element illustrates the organization data estate and potential data sources and targets for a data science project.

For teams with more familiarity with MLOps and Azure, we recommend to have three environments. If you want to learn more about best practices, you can visit Azure CloudFramework BestPractices. This page explains how to setup an Azure architecture for your machine learning projects.

2024年10月11日 · Azure Machine Learning provides two fully managed, cloud-based virtual machines (VMs) that are specifically designed for machine learning tasks: A compute instance is a single VM...

2024年3月18日 · You can deploy Machine learning models to Machine Learning compute or to other Azure services such as Azure Kubernetes Service (AKS). This article provides architectural recommendations for making informed decisions when you use Machine Learning to train, deploy, and manage machine learning models.

Azure Machine Learning supports extensive, diverse capabilities for robust AI and ML development. Streamline prompt engineering projects and build language model–based applications. Automatically build machine learning models with speed and scale. Collaborate and streamline model management with machine learning operations (MLOps).