Overview: The Java ecosystem now offers a wide variety of ML frameworks - from lightweight toolkits for data mining to ...

Despite the excitement surrounding generative AI, the data shows that scientific research is still powered primarily by ...

In today's digital landscape, organizations face an unprecedented challenge: managing and protecting ever-growing volumes of data spread across multiple environments. As someone deeply involved in ...

Data classification is an essential pre-requisite to data protection, security and compliance. Firms need to know where their data is and the types of data they hold. Organisations also need to ...

When it comes to managing data, we need to know where it is – but we also need to know what it is. With the rise in regulatory controls, enterprises now pay more attention to data sovereignty, ...

Unveiled November 10, ML.NET 2.0 arrived in tandem with a new version of the ML.NET Model Builder, a visual developer tool for building machine learning models for .NET applications. The Model Builder ...

Microsoft shipped ML.NET 3.0, enhancing deep learning and data processing scenarios in the company's machine language framework that lets devs create AI-infused apps completely within the .NET ...

Dr. Chris Hillman, Global AI Lead at Teradata, joins eSpeaks to explore why open data ecosystems are becoming essential for enterprise AI success. In this episode, he breaks down how openness — in ...

As organizations evolve, traditional data classification—typically designed for regulatory, finance or customer data—is being stretched to accommodate employee data. While classification processes and ...