RIT researchers publish a paper in Nature Scientific Reports on a new tree-based machine learning algorithm used to predict chaos.
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 ...
New forms of fentanyl are created every day. For law enforcement, that poses a challenge: How do you identify a chemical you've never seen before? Researchers at Lawrence Livermore National Laboratory ...
Interpretable AI model could offer new insights into why medicines cause certain side effects, helping to improve future drug safety predictions.
Read more about AI-driven learning analytics struggle to deliver measurable gains in higher education on Devdiscourse ...
The Southern Maryland Chronicle on MSN
How are QA teams using machine learning to predict test failures in real time?
QA teams now use machine learning to analyze past test data and code changes to predict which tests will fail before they run. The technology examines patterns from previous test runs, code commits, ...
Researchers developed a machine-learning-assisted approach to improve micro-electro-discharge machining (µ-EDM) of the ...
Microgrids play a growing role in modern power systems, supporting renewable integration, local resilience, and decentralized ...
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