Northwestern Engineering faculty and students participated in the annual forum for advances in theory, empirics, and ...

Machine learning is an integral part of high-stakes decision-making in a broad swath of human-computer interactions. You ...

Machine learning–driven approaches for predicting T-cell–mediated immunity and beyond.. If you have the appropriate software installed, you can download article citation data to the citation manager ...

Typical Azure Machine Learning Project Lifecycle (source: Microsoft). At the upcoming Visual Studio Live! @ Microsoft HQ 2025 conference in Redmond, Eric D. Boyd, founder and CEO of responsiveX, will ...

This consists of 15 biochemical tests, including serum phosphate. Our aim was to understand if abnormalities in serum phosphate could be predicted, using a machine learning algorithm (MLA) by other ...

The previous study focused on predicting stock prices using machine learning and deep learning models. However, no study tackled a comparison between machine learning and deep learning to enhance the ...

Methods: An empirical dataset collected was used to examine self-efficacy among secondary school students in Muslim societies. Four machine learning algorithms-Decision Tree, Random Forest, XGBoost, ...

The predictive model is trained and tested using various machine learning (ML) and deep learning (DL) algorithms to characterize the learning behavior of students according to their study variables.

Three new books warn against turning into the person the algorithm thinks you are.

This paper aims to explore the effectiveness of JFLAP as a pedagogical tool for automata theory and its impact on student performance. We implement machine learning algorithms to predict and analyze ...