DevOps for Machine Learning
Explore DevOps principles for effective collaboration between data scientists and software engineers in machine learning projects, focusing on automated pipelines and best practices.
VMS: Interactive Visualization to Support the Sensemaking and Selection of Predictive Models
Explore interactive visualization for comparing and selecting predictive models, integrating performance, instance, and feature-level analysis to support informed decision-making in machine learning.
The Essentials of Evaluating LLM Systems
Master practical techniques for evaluating LLM systems, from defining criteria and selecting evaluators to implementing heuristic models and conducting nuanced assessments for enterprise AI applications.
Koopman Operator Theory Based Machine Learning of Dynamical Systems
Explore Koopman Operator Theory for machine learning of dynamical systems, covering applications in fluid dynamics, power grids, network security, and more.
QML and Neuroimaging AI/ML for Alzheimer's Prediction
Explore cutting-edge AI/ML and quantum computing applications in Alzheimer's prediction using neuroimaging. Learn about multimodal approaches, recent research, and industry developments in QML for medical imaging.
Balancing Interpretability and Predictive Accuracy in Mathematical Models of T Cell Activation
Explore mathematical modeling approaches for T cell activation, examining the trade-offs between model interpretability and accuracy in immunological systems.