I was very happy to be invited to give an invited talk at the 8th Asian Conference on Machine Learning (ACML 2016) in Hamilton, New Zealand.

The talk was on Massive Online Analytics for the Internet of Things (IoT). 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 presented an overview of data stream mining, and I introduced MOA as the most popular open source tool for data stream mining.



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