Tutorial, Victoria University of Wellington
This tutorial introduced core concepts in machine learning for data streams, with an emphasis on concept drift and evolving data. Attendees engaged with hands-on examples using CapyMOA through practical demonstrations.
Demonstration, Alfândega Porto Congress Centre, Porto, Portugal
This demonstration introduced key concepts in machine learning for data streams, including online classification and regression, prediction intervals, anomaly detection, and concept drift. Using CapyMOA, we illustrated how these tasks can be addressed within a unified and practical framework for streaming data analysis.
Tutorial, Clock Tower Centennial Hall, Kyoto University
Our tutorial covers essential aspects of machine learning for streaming data, focusing on the challenges of concept drift detection and evolving data streams. Attendees explored hands-on examples using CapyMOA, an open-source library with a Python API, including practical exercises and real-time implementation demonstrations.
Tutorial, Auckland University of Technology
This tutorial highlighted the latest research topics in streaming data, with a focus on adaptive algorithms for evolving environments. Practical demonstrations using CapyMOA showed attendees how to implement and assess algorithms for delayed labeled streams and real-time applications. The session featured interactive exercises and multiple examples.