We’ve gotten pretty good at building machine learning models. From legacy platforms like SAS to modern MPP databases and Hadoop clusters, if you want to train up regression or classification models, ...

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 ...

Until now, designing complex metamaterials with specific mechanical properties required large and costly experimental and simulation datasets. The method enables ...

Public safety and efficient urban planning remain pressing challenges in Nigeria. From congested cities to crime hotspots and disaster-prone areas caused mostly by floods, authorities often lack the ...

Overview: AI in financial services uses machine learning and automation to analyze data in real time, improving speed, accuracy, and decision-making across bank ...

Researchers in Slovakia have demonstrated a machine-learning framework that predicts PV inverter output and detects anomalies using only electrical and temporal data, achieving 100% accuracy in ...

The data science and machine learning technology space is undergoing rapid changes, fueled primarily by the wave of generative AI and—just in the last year—agentic AI systems and the large language ...

Sticking to an exercise routine is a challenge many people face. But a research team is using machine learning to uncover what keeps individuals committed to their workouts. Sticking to an exercise ...

We've been reactive toward security risks for years, waiting for an incident to occur before responding. But what if I told you that a proactive approach, identifying and mitigating security risks ...