Researchers developed a two-stage ML model to predict coating degradation by linking environmental factors to physical changes and corrosion. The framework enables more accurate, data-driven ...

While the technological promise of AI is clear, the study highlights major constraints to deployment, particularly in the ...

Purdue Agriculture researchers are harnessing the power of artificial intelligence (AI) and machine learning (ML) to amplify ...

Examples include logistic regression, random forests, and support vector machines. Use cases: Fraud detection, customer segmentation, spam filtering, sentiment analysis, and medical diagnosis.

In the study, published by Coastal Engineering Journal, Goda showed random forest models - a machine learning algorithm that uses decision trees ... Learn more here We endeavour to provide the ...

Opinion: Lidiya Mishchenko and Pooya Shoghi explain how to bridge a gap preventing successful patent claims to protect new ...

A new machine learning approach tries to better emulate the human brain, in hopes of creating more capable agentic AI.

ML-powered retail media solutions optimize product visibility, enhance shopping experiences and create wins for sellers, ...

More information: Zhenghao Yin et al, Experimental quantum-enhanced kernel-based machine learning on a photonic processor, Nature Photonics (2025). DOI: 10.1038/s41566-025-01682-5 ...

Applied Analytics professor Siddhartha Dalal discusses the impacts of applied technologies on real-life risk management.

Properly managing forests requires tools that offer up-to-date information on forest dynamics.