Sep 23–26, 2019
Heitor Murilo Gomes

Heitor Murilo Gomes
Researcher, Télécom ParisTech

Website

Heitor Murilo Gomes is a researcher at Télécom ParisTech focusing on machine learning—particularly evolving data streams, concept drift, ensemble methods, and big data streams. He co-leads the StreamDM open data stream mining project.

Sessions

2:05pm2:45pm Thursday, September 26, 2019
Location: 3B - Expo Hall
Secondary topics:  Streaming and IoT, Telecom, Temporal data and time-series analytics
Heitor Murilo Gomes (Télécom ParisTech), Albert Bifet (Télécom ParisTech)
In this talk, we show how to develop a machine learning pipeline for streaming data using the StreamDM framework (https://github.com/huawei-noah/streamDM). We also introduce how to use StreamDM for supervised and unsupervised learning tasks, show examples of online preprocessing methods, and how to expand the framework adding new learning algorithms or preprocessing methods. Read more.

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