Which Machine Learning Models Are Most Used In Crypto Signal Generation?

Machine learning is transforming how crypto traders create and understand signals. From supervised models such as Random Forests and Gradient Boosting Machines to sophisticated deep learning hybrids ...
Scientific Research Publishing

Research on Prediction of Air Quality CO Concentration Based on Python Machine Learning ()

Wang, Z. (2025) Research on Prediction of Air Quality CO Concentration Based on Python Machine Learning. Advances in Internet ...
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 ...
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, ...
IEEE

Solar Energy Forecasting Using Machine Learning Techniques for Enhanced Grid Stability

Abstract: The increasing integration of solar photovoltaic (PV) systems into modern energy grids presents significant challenges due to the intermittent and weather-dependent nature of solar energy ...
GitHub

Imprecise Probabilistic Machine Learning

“There are known knowns. There are known unknowns. But there are also unknown unknowns—things we do not yet realize we do not know.”—Donald Rumsfeld (2002) While modern machine learning (ML) ...
Visual Studio Magazine

Kernel Ridge Regression with Stochastic Gradient Descent Training Using JavaScript

Dr. James McCaffrey presents a complete end-to-end demonstration of the kernel ridge regression technique to predict a single numeric value. The demo uses stochastic gradient descent, one of two ...
The EMBO Journal

Predicting natural variation in the yeast phenotypic landscape with machine learning

Peer ReviewDownload a summary of the editorial decision process including editorial decision letters, reviewer comments and author responses to feedback. Most organismal traits result from the complex ...
C&EN

From Reaction Stoichiometry to Life Cycle Assessment: Decision Tree-Based Estimation Tool

Creative Commons (CC): This is a Creative Commons license. Attribution (BY): Credit must be given to the creator. Decision-making during the early stages of research and development (R&D) should be ...
Frontiers

Efficient tree species classification using machine and deep learning algorithms based on UAV-LiDAR data in North China

Introduction: The unmanned aerial vehicle -based light detection and ranging (UAV-LiDAR) can quickly acquire the three-dimensional information of large areas of vegetation, and has been widely used in ...