Enterprises can now train custom AI models from production workflows — no ML team required

Empromptu's Alchemy Models turns enterprise AI application outputs into a fine-tuning pipeline, letting companies own custom ...

Machine-learning method maps the uncertainty of biodiversity scenarios: The Bigfoot connection

To effectively protect biodiversity in an era of climate change, ecologists first have to know where animal and plant species ...
AZoSensors

Wearable Sensors Enable Early Behavior Risk Prediction

Wearable sensors and machine learning can forecast self-injurious behavior in autistic youth, enabling proactive ...
Hosted on MSN

New 2026 AI Laws Reshape Machine Learning in Finance

The financial landscape of 2026 is defined by a paradox: machine learning systems are now more powerful and autonomous than ever, yet they operate under the strictest regulatory scrutiny in history.
Hosted on MSN

AI is digging deeper into geoscience research

From mineral exploration to seismic interpretation, AI is reshaping how geoscientists work with complex, multi-source data. Machine learning models, generative AI, and prompt engineering are enabling ...
IEEE

Advancing Shallow Water Bathymetry Estimation in Coral Reef Areas via Stacking Ensemble Machine Learning Approach

Abstract: Satellite-derived bathymetry technology plays a pivotal role in estimating shallow water depths. Although traditional machine learning (ML) models are extensively applied in water depth ...
Frontiers

An explainable ensemble machine learning model using baseline blood transcriptomics to predict Parkinson's disease motor progression

Predicting Parkinson's disease (PD) motor progression remains challenging despite advances in neuroimaging. Blood-based transcriptomic profiling offers a more accessible and cost-effective alternative ...
Scientific Research Publishing

Dietterich, T.G. (2000) Ensemble Methods in Machine Learning. First International Workshop, MCS 2000, Cagliari, 21-23 June 2000, 1-15.

ABSTRACT: Accurate land use/land cover (LULC) classification remains a persistent challenge in rapidly urbanising regions especially, in the Global South, where cloud cover, seasonal variability, and ...
C&EN

Advanced Multi-Parameter Prediction of Coal Quality Using LIBS and Ensemble Machine Learning Techniques

The LIBS measurement system primarily consisted of an Nd:YAG laser (Dwa-200, Beijing LeiBao Photoelectric Technology Co., Ltd., China), a multichannel spectrometer (AvaSpec-ULS2048, Avantes, ...
IEEE

Utilization of Ensemble Techniques in Machine Learning to Predict the Porosity and Hardness of Plasma-Sprayed Ceramic Coating

Abstract: Ceramic coatings play a vital role in protecting steel components by significantly enhancing their corrosion and wear resistance, thereby extending service life. The performance of these ...