Artificial intelligence is built on the foundation of machine learning (ML) models. These models are software programs designed to classify data, identify data patterns, spot anomalies in data sets, ...

Ishaan Dokania, a sixth-grader from Oregon, is exploring lithium resource identification using satellite imagery and machine ...

A strong foundation in mathematics plays a critical role in understanding artificial intelligence and adapting to ongoing technological change. Math underpins many machine learning basics, shaping how ...

A precise streamflow forecast is crucial in hydrology for flood alerts, water quantity and quality management, and disaster preparedness. Machine learning (ML) techniques are commonly employed for ...

Why accuracy and strong backtests can mislead in ML—and why reproducibility, leakage-safe validation, and economic evidence ...

This presentation explores how machine learning can be used to model storm surge hazards at continental and global scales. Participants will learn why broadscale storm surge information is important ...

HSBC says it’s designed a machine-learning model to predict the direction of the most important financial instrument in global markets.

Earth System Models (ESM) are our main tool for projecting the impacts of climate change. However, running these models at sufficient resolution for local-scale risk-assessments is not computationally ...

Quantum computers promise to solve problems that stump even the most powerful supercomputers, but the machines themselves are ...

A study published in Discover Artificial Intelligence used logistic regression, random forest and support vector machine (SVM ...

Machine learning predicted activated clotting time during AF ablation, with deep learning achieving 81% accuracy.

A proposed machine learning framework for metabolic dysfunction-associated steatotic liver disease may improve personalized risk prediction.