Presented By O’Reilly and Cloudera
Make Data Work
21–22 May 2018: Training
22–24 May 2018: Tutorials & Conference
London, UK
Emre Velipasaoglu

Emre Velipasaoglu
Principal Data Scientist, Lightbend

Website

Emre Velipasaoglu is principal data scientist at Lightbend. A machined learning expert, Emre previously served as principal scientist and senior manager at Yahoo! Labs. He has authored 23 peer-reviewed publications and nine patents in search, machine learning, and data mining. Emre holds a PhD in electrical and computer engineering from Purdue University and completed postdoctoral training at Baylor College of Medicine.

Sessions

14:55–15:35 Wednesday, 23 May 2018
Machine-learned model quality monitoring in fast data and streaming applications
Data science and machine learning, Expo Hall, Streaming systems and real-time applications
 Location: Expo Hall Level: Intermediate
Secondary topics:  Managing and Deploying Machine Learning
Emre Velipasaoglu (Lightbend)
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Most machine learning algorithms are designed to work on stationary data, but real-life streaming data is rarely stationary. Models lose prediction accuracy over time if they are not retrained. Without model quality monitoring, retraining decisions are suboptimal and costly. Emre Velipasaoglu reviews monitoring methods, focusing on their applicability in fast data and streaming applications. Read more.