The CDC has quietly been building a modern AI infrastructure designed to reshape how public health data is collected, ...
Individual prediction uncertainty is a key aspect of clinical prediction model performance; however, standard performance metrics do not capture it. Consequently, a model might offer sufficient ...
Angie received her M.S. in computer science with a concentration in machine learning from The George Washington University ...
This list is continuously updated. Pull requests welcome — please follow CONTRIBUTING.md. A curated list of 500+ AI/ML/DL/CV/NLP projects and resources (tutorials, repos, datasets, papers-with-code).
Abstract: In Federated Learning (FL) systems, clients share updates derived from their local data with the server while maintaining privacy. The server aggregates these updates to refine the global ...
Abstract: Prioritizing or reweighting important samples has been recognized as an effective means of improving the efficiency of deep-reinforcement learning (DRL) algorithms. However, many existing ...
An Industrial IoT (IIoT) predictive maintenance system that simulates factory equipment, monitors sensor data in real-time, and uses Machine Learning to predict equipment failures before they happen ...
Start your journey into machine learning with EEG time-series data in this easy-to-follow Python project. Perfect for beginners looking to explore brain signal analysis! #MachineLearning #EEG ...
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