Businesspeople need to demand more from machine learning so they can connect data scientists’ work to relevant action. This requires basic machine learning literacy — what kinds of problems can ...

In this paper we investigate oil market volatility prediction using a comprehensive data set of 205 variables spanning macroeconomic, financial, energy-related and sentiment indicators. We employ ...

Development and Portability of a Text Mining Algorithm for Capturing Disease Progression in Electronic Health Records of Patients With Stage IV Non–Small Cell Lung Cancer Emerging evidence suggests ...

In a recent study published in Scientific Reports, researchers developed a machine learning-based heart disease prediction model (ML-HDPM) that uses various combinations of information and numerous ...

Abhijeet Sudhakar develops efficient Mamba model training for machine learning, improving sequence modelling and ...

Driverless AI really is able to create and train good machine learning models without requiring machine learning expertise from users. Machine learning, and especially deep learning, have turned out ...

Data volumes continue to explode with the global “datasphere” – the total amount of data created, captured, replicated and consumed – growing at more than 20 percent a year to reach approximately 291 ...