Dr. James McCaffrey from Microsoft Research presents a full-code, step-by-step tutorial on using the LightGBM tree-based system to perform binary classification (predicting a discrete variable that ...

A hybrid model combining LM, GA, and BP neural networks improves TCM's diagnostic accuracy for IPF, achieving 81.22% ...

Ben Khalesi covers the intersection of artificial intelligence and everyday tech at Android Police. With a background in AI and data science, he enjoys making technical topics approachable for those ...

Discover the power of predictive modeling to forecast future outcomes using regression, neural networks, and more for improved business strategies and risk management.

When it comes to managing data, we need to know where it is – but we also need to know what it is. With the rise in regulatory controls, enterprises now pay more attention to data sovereignty, ...

For more than 20 years in experimental particle physics and astrophysics, machine learning has been accelerating the pace of science, helping scientists tackle problems of greater and greater ...

Based Detection, Linguistic Biomarkers, Machine Learning, Explainable AI, Cognitive Decline Monitoring Share and Cite: de Filippis, R. and Al Foysal, A. (2025) Early Alzheimer’s Disease Detection from ...

Overview: In 2025, Java is expected to be a solid AI and machine-learning language.Best Java libraries for AI in 2025 can ease building neural networks, predict ...

Machine learning is a subfield of artificial intelligence, which explores how to computationally simulate (or surpass) humanlike intelligence. While some AI techniques (such as expert systems) use ...

Theoretical physicists use machine-learning algorithms to speed up difficult calculations and eliminate untenable theories—but could they transform what it means to make discoveries? Theoretical ...