InfoWorld

AI and machine learning outside of Python

Python might be the default for most AI and machine learning development, but what about other popular languages? Here’s what ...

Heat wave predictions months in advance with machine learning

With heat waves among Europe's deadliest climate hazards, a team of scientists led by CMCC has developed a prediction system capable of providing helpful information four to seven weeks before summer, ...
IEEE

Ensemble Learning and Deep Neural Networks for Enhanced Credit Card Fraud Detection

Abstract: Higher digital payment volume and escalating fraud patterns create obstacles for the financial industry when detecting credit card fraud. Machine learning approaches enable the sector to ...
New Electronics

Alif Semiconductor providing support for ExecuTorch Runtime in Ensemble MCUs

Alif Semiconductor, a supplier of Artificial Intelligence and Machine Learning (AI/ML) microcontrollers (MCUs) and fusion ...

Alif Semiconductor elevates generative AI at the edge with new support for ExecuTorch Runtime in its Ensemble MCUs

Alif Semiconductor®, the leading global supplier of secure, connected, power efficient Artificial Intelligence and Machine ...

Explainable AI Market Will Reach $34.6 Billion by 2033 - Interview Kickstart's Adds XAI Specialization to Machine Learning Course

SANTA CLARA, CA - October 30, 2025 - - The global demand for Explainable AI (XAI) is accelerating as organizations seek ...
Scientific Research Publishing

Estimating Average and Heterogeneous Effects of Special Education: A Causal Machine Learning Perspective ()

Causal Machine Learning (CML) unites ML techniques with CI in order to take advantage of both approaches’ strengths. CML ...
AZoSensors on MSN

ML and Volume Modeling Boosts Corn Biomass Prediction

Advanced UAV sensor integration and machine learning may improve corn AGB predictions, providing scalable solutions for ...
pv magazine International

Machine learning-based fault detection technique for bifacial PV

CNN and random forest model to detect multiple faults in bifacial PV systems, including dust, shading, aging, and cracks. Using simulated I-V curves and a 180-day synthetic dataset, the model achieved ...
Devdiscourse

AI-powered forecasting boosts retail efficiency: LSTM outshines traditional models

Demand forecasting remains one of the most complex challenges in retail management. As consumer behavior evolves rapidly, ...

Jiaying Huang Explores Forecasting Strategies to Optimize Resource Scheduling in Cloud Platforms

A forecasting-driven framework integrates ARIMA, LSTM, and ensemble learning to optimize cloud resource scheduling. By predicting CPU, memory, ...
Frontiers

From Traditional Metabolic Markers to Ensemble Learning: Comparative Application of Machine Learning Models for Predicting NAFLD Risk in Adolescents

The final, formatted version of the article will be published soon. Background: Non-alcoholic fatty liver disease (NAFLD) is increasingly prevalent among adolescents and poses a major public health ...