Microsoft has expanded the data-analysis offerings on its Azure cloud, offering a machine learning service to help organizations derive more insight from mountains of unstructured data. The new ...

AI thrives on data but feeding it the right data is harder than it seems. As enterprises scale their AI initiatives, they face the challenge of managing diverse data pipelines, ensuring proximity to ...

The technology that turns petabytes of data into useful features that machine learning models can use already works on Azure. As organizations start to make more extensive use of machine learning, ...

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...

Nearly seven years after its debut as a preview, the Visual Studio Code extension for Azure Machine Learning has hit general availability. "You can use your favorite VS Code setup, either desktop or ...

Microsoft’s recent Azure Open Source Day showed off a new reference application built using cloud-native tools and services, with a focus on Microsoft’s own open source tools. The app was built to be ...

NVIDIA AI Enterprise, available on the Microsoft Azure Marketplace, announced this week that it has expanded support for secure development and deployment of artificial intelligence with a new Azure ...

In today’s fast-changing data landscape, having a strong data system and advanced analytical tools is key to getting valuable insights and staying ahead of the competition. The data lakehouse ...

To create effective machine learning and deep learning models, you need copious amounts of data, a way to clean the data and perform feature engineering on it, and a way to train them on your data in ...

Data volumes continue to explode with the global “datasphere” – the total amount of data created, captured, replicated and consumed – growing at more than 20 percent a year to reach approximately 291 ...

Quality data is at the heart of the success of enterprise artificial intelligence (AI). And accordingly, it remains the main source of challenges for companies that want to apply machine learning (ML) ...