IEEE

Predicting Pipe Failures: A Machine Learning Approach to Asset Management in District Heating

Abstract: As district heating networks (DHNs) across Europe near or surpass their intended service life, the need for proactive, data-driven maintenance and replacement planning is increasing. This ...

Not all MMM tools are equal: Meridian, Robyn, Orbit, and Prophet explained

These open-source MMM tools solve different measurement problems, from budget optimization to forecasting and preprocessing.
The Verge

The algorithm failed music

Music recommendation algorithms were supposed to help us cut through the noise, but they just served us up slop. If you buy something from a Verge link, Vox Media may earn a commission. See our ...
Education Week

Ed. Colleges Are Granting Fewer Degrees, Potentially Affecting the Teacher Pipeline

As more American teachers reach retirement age, new data suggest fewer teachers who generally have less preparation are ready to replace them. The majority of U.S. teachers are prepared for the ...
NextBigFuture

Looking at Current AI Learning Frameworks to Create Learning Pipelines to Achieve Superintelligence

Andrej Karpathy says that reinforcement learning is still terrible but better than all other AI learning approaches. Elon Musk believes there is a 10% chance that XAI Grok 5 can achieve AGI. Musk ...
GitHub

BEED Benchmark: A Modular Machine Learning Pipeline for EEG-based Epileptic Seizure Detection

BEED (Biomedical EEG Epilepsy Detection) Benchmark is a comprehensive, modular implementation for benchmarking machine learning algorithms on EEG-based epileptic seizure detection datasets. This ...
Cloud Security Alliance

The Hidden Security Threats Lurking in Your Machine Learning Pipeline

Machine learning operations (MLOps) have rapidly evolved from experimental workflows to production-critical systems powering everything from fraud detection to autonomous vehicles. But as ...
Frontiers

Machine learning pipeline for microparticle size classification in self-mixing interferometric signals for flow cytometry

Self-mixing interferometry (SMI) is an emerging optical sensing technique for detecting and classifying microparticles in non-contact and label-free flowmetry applications. High precision and ...
Scientific Research Publishing

Yang, M.D. and Su, T.C. (2008) Automated Diagnosis of Sewer Pipe Defects Based on Machine Learning Approaches. Expert Systems with Applications, 35, 1327-1337.

ABSTRACT: Regular pipeline inspections are crucial for timely identification of critical defects and ensuring pipeline integrity. To address the challenges of detecting defects in PE gas pipelines ...
GitHub

ChemXploreML - Chemistry eXploration with Machine Learning

ChemXploreML is a user-friendly desktop application specifically designed to bring the power of machine learning to chemistry research. It streamlines the entire machine learning pipeline for ...
Frontiers

Machine learning technique for the identification of two-phase (oil-water) flow patterns through pipelines

1 School of Mechanical Engineering, Universidad Industrial de Santander, Bucaramanga, Colombia 2 Industrial Multiphase Flow Laboratory (LEMI), Mechanical Engineering Department, São Carlos School of ...