Adaptive Machine Learning for Data Streams

Título:  Adaptive Machine Learning for Data Streams

Ponente: Albert Bifet (University of Waikato)

Organizador: Alejandro Rabasa

Fecha: Lunes 25 de enero de 2021 a las 9:00 horas.

Lugar:  Online. meet.google.com/crb-qgqs-ifh

Abstract: Big Data and the Internet of Things (IoT) have the potential to fundamentally shift the way we interact with our surroundings. The challenge of deriving insights from the Internet of Things (IoT) has been recognized as one of the most exciting and key opportunities for both academia and industry. Advanced analysis of big data streams from sensors and devices is bound to become a key area of data mining research as the number of applications requiring such processing increases. Dealing with the evolution over time of such data streams, i.e., with concepts that drift or change completely, is one of the core issues in stream mining. In this talk, I will present an overview of data stream mining, and I will introduce some popular open source tools for data stream mining.