MIT researchers have identified significant examples of machine-learning model failure when those models are applied to data ...

While demand planning accuracy currently hovers around 60%, DLA officials aim to push that baseline figure to 85% with the help of AI and ML tools. Improved forecasting will ensure the services have ...

Overview: Focuses on skills, projects, and AI readiness, not hypeCovers degrees, certificates, and online programmesHelps ...

“Drought is different during spring versus summer versus fall. There’s so much data that we can have available to us, and so ...

Learn how to find and make the best use of valuable insights buried in your company’s databases.

In the life sciences and healthcare industries, the speed of innovation impacts how soon new products, medications and ...

Who is a data scientist? What does he do? What steps are involved in executing an end-to-end data science project? What roles are available in the industry? Will I need to be a good ...

Review re-maps multi-view learning into four supervised scenarios and three granular sub-tiers, delivering the first unified blueprint for researchers to navigate classification, clustering, ...

SolarRock Technologies founder Edidiong Mbong seeks pre-seed funding to deploy AI and machine learning to solve challenges in ...

Less instrumentation. More insight. Physics-informed virtual sensors are shifting condition monitoring from isolated pilots ...

Dhruv Shenai investigates how machine learning and lab automation are transforming materials science at Cambridge ...