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 ...

Abstract: Data stream learning is an emerging machine learning paradigm designed for environments where data arrive continuously and must be processed in real time. Unlike traditional batch learning, ...

This project was developed as part of my Master's programm at Heilbronn University. The goal is to classify different oil samples (e.g. olive oil, sunflower oil) based on their fluorescence and ...

The ability to anticipate what comes next has long been a competitive advantage -- one that's increasingly within reach for developers and organizations alike, thanks to modern cloud-based machine ...

Machine learning is a multibillion-dollar business with seemingly endless potential, but it poses some risks. Here's how to avoid the most common machine learning mistakes. Machine learning technology ...

One of the best ways to reduce your vulnerability to data theft or privacy invasions when using large language model artificial intelligence or machine learning, is to run the model locally. Depending ...

Abstract: This paper presents a dynamic selector model for data workload prediction. A main function responsible for selecting the most accurate Machine Learning Algorithm (e.g., Linear Regression, ...

In the past few years, HR has seen a significant transformation driven by the rise of machine learning tools and technology. 1 These tools extract insights, patterns, and predict trends from massive ...