This project demonstrates the implementation of Simple Linear Regression, a supervised machine learning algorithm, to predict student exam scores based on the number of hours studied. The objective is ...
Objective: This study evaluated the feasibility of using a smartphone app to predict mental health risks in non-clinical adolescents by integrating active and passive data streams within a machine ...
Machine Learning in Action: Tools, Techniques, and Industrial Cases Bring machine learning to life with Machine Learning in Action. This hands-on course teaches you how to build and apply eight key ...
ABSTRACT: The rapid proliferation of Internet of Things (IoT) devices in healthcare systems has introduced critical security challenges, particularly in resource-constrained environments typical of ...
Abstract: The rise of graph-structured data has driven major advances in Graph Machine Learning (GML), where graph embeddings (GEs) map features from Knowledge Graphs (KGs) into vector spaces, ...
Machine learning is an essential component of artificial intelligence. Whether it’s powering recommendation engines, fraud detection systems, self-driving cars, generative AI, or any of the countless ...
Copyright: © 2025 The Author(s). Published by Elsevier Ltd. Machine learning for health data science, fuelled by proliferation of data and reduced computational ...
EXtreme Gradient Boosting (XGBoost), a machine learning model, outperformed more traditional methods for predicting composite major adverse events (MAEs) and many individual events in patients ...
For the last two years, conversations about AI in education have tended to fall into two camps: excitement about efficiency or fear of replacement. Teachers worry they’ll lose authenticity. Leaders ...
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