Overview: Free YouTube channels provide structured playlists covering AI, ML, and analytics fundamentals.Practical coding demonstrations help build real-world d ...

Abstract: Machine learning (ML) models were used to determine the moisture content (MC) for multiple grains and seeds after training on a large dataset obtained through several decades of research.

Supervised learning algorithms like Random Forests, XGBoost, and LSTMs dominate crypto trading by predicting price directions or values from labeled historical data, enabling precise signals such as ...

Abstract: This paper analyzes the performance of different LDA combinations with machine learning algorithms in predicting diabetes based on clinical data. The analysis involves patient records with ...

Are Machine Learning (ML) algorithms superior to traditional econometric models for GDP nowcasting in a time series setting? Based on our evaluation of all models from both classes ever used in ...

Data Science Program, University of Delaware, Newark, Delaware 19716, United States Department of Materials Science and Engineering, University of Delaware, Newark, Delaware 19716, United States ...

A recent study, “Picking Winners in Factorland: A Machine Learning Approach to Predicting Factor Returns,” set out to answer a critical question: Can machine learning techniques improve the prediction ...

Postpartum depression (PPD) is a common and serious mental health complication after childbirth, with potential negative consequences for both the mother and her infant. This study aimed to develop an ...

View all available purchase options and get full access to this article. The following represents disclosure information provided by authors of this manuscript. All relationships are considered ...

One of the current hot research topics is the combination of two of the most recent technological breakthroughs: machine learning and quantum computing. An experimental study shows that already ...