Presented By O’Reilly and Cloudera
Make Data Work
September 11, 2018: Training & Tutorials
September 12–13, 2018: Keynotes & Sessions
New York, NY
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 coleads the streamDM open data stream mining project.

Sessions

3:30pm–4:10pm Thursday, 09/13/2018
Machine learning for nonstationary streaming data using Structured Streaming and StreamDM
Location: 1E 07/08 Level: Intermediate
Secondary topics:  Temporal data and time-series analytics
Heitor Murilo Gomes (Télécom ParisTech), Albert Bifet (Télécom ParisTech)
The StreamDM library provides the largest collection of data stream mining algorithms for Spark. Heitor Murilo Gomes and Albert Bifet explain how to use StreamDM and Structured Streaming to develop, apply, and evaluate learning models specially for nonstationary streams (i.e., those with concept drifts). Read more.