Who needs rewrites? This metadata-powered architecture fuses AI and ETL so smoothly, it turns pipelines into self-evolving ...

And the emergence and democratisation of machine learning has given companies many new opportunities and capabilities. MLOps brings these two important and powerful disciplines together.

Microsoft is wrapping its Cognitive Services machine learning platform as business-focused services.

In coordination with cloud technology, AI-driven predictive monitoring is changing the face of future DevOps.

Machine learning should also be easier to integrate into existing DevOps workflows with the new MLOps, which is described as DevOps for machine learning.

Additionally, users can leverage Azure DevOps or GitHub Actions to schedule, manage and automate their machine learning pipelines and perform advanced data-drift analysis to improve a model's ...

Typical Azure Machine Learning Project Lifecycle (source: Microsoft). At the upcoming Visual Studio Live! @ Microsoft HQ 2025 conference in Redmond, Eric D. Boyd, founder and CEO of responsiveX, will ...

This capability allows customers to build models with Azure Machine Learning anywhere, including on-premises, multi-cloud environments, and at the edge.

New previews for Azure OpenAI Service, AI dashboards in Azure Machine Learning and a web application routing add-in for Azure Kubernetes Service were among the biggest Azure announcements from ...

Azure SQL Database Machine Learning services preview Support for R models inside SQL Database makes it seamless for data scientists to develop and train models in Azure Machine Learning and deploy ...