Data is fundamental to hydrological modeling and water resource management; however, it remains a major challenge in many ...

As web applications become more sophisticated to meet our daily needs, such as shopping and communication, they also become more vulnerable to data breaches. In 2024, web applications were the target ...

The absence of reliable data on fundamental economic indicators (e.g. real GDP), combined with structural shifts in the economy, can severely constrain the ability to conduct accurate macroeconomic ...

Interview Kickstart today announced the launch of its Advanced Machine Learning Program, a specialized interview preparation track designed for engineers and data professionals preparing for machine ...

Objective This study reviewed the current state of machine learning (ML) research for the prediction of sports-related injuries. It aimed to chart the various approaches used and assess their efficacy ...

QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...

In recent years, JupyterLab has rapidly become the tool of choice for data scientists, machine learning (ML) practitioners, and analysts worldwide. This powerful, web-based integrated development ...

New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...

Lithium-ion batteries have become the quiet workhorses of the energy transition, but the way they are designed and tested has long been slow, expensive, and heavily empirical. Machine learning is now ...

Microfactories are not just smaller replicas of mega-factories. They operate with radically different assumptions. Data is ...