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 ...
Frontiers

Advancing Computational Material Science and Mechanics through Integrated Deep Learning Models

The field of computational materials science has been profoundly transformed by integrating deep learning and other machine learning methodologies. These sophisticated data-driven approaches have ...
Devdiscourse

The Art of Forecasting: IMF’s Path to Accurate Real-Time GDP Predictions for China

The IMF study on Parameter Proliferation in Nowcasting shows that simpler, well-structured models guided by economic ...
IEEE

Prediction of Asthma Using Machine Learning Algorithms

Abstract: Asthma, a prevalent chronic respiratory condition, poses significant challenges to public health worldwide. Accurate and early prediction of asthma risk can greatly aid healthcare ...
Devdiscourse

New AI forecasting model promises greater stability for Kenya’s volatile food prices

Kenya’s food markets are known for extreme volatility influenced by weather shocks, inflation, currency fluctuations, and ...
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 ...
IEEE

Efficient Algorithms for Estimating the Parameters of Mixed Linear Regression Models

Abstract: Mixed linear regression (MLR) models nonlinear data as a mixture of linear components. When noise is Gaussian, the Expectation-Maximization (EM) algorithm is commonly used for maximum ...