---
title: Video from Camunda Community Summit 2021 - Predictive Process Monitoring Made Easy
description: Stefan and Nico will present a plugin that equips Camunda with machine learning techniques for predictive process monitoring. Watch on-demand.
image: https://page.camunda.com/hubfs/CCSummit_OnDemand.png
---

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## Predictive Process Monitoring Made Easy

| *Intermediate/Advanced Track* Stefan and Nico will present a plugin that equips Camunda with machine learning techniques for predictive process monitoring. Features include: - Display activity, time and risk prediction in the Cockpit view - Training, version control and parametrization of ML algorithms - Ensemble Learning – Easy expandability in means of predictions types, algorithms - Automated hyperparameter optimization |   | ##### **Resources** - [Download the Slides](https://www.slideshare.net/camunda/predictive-process-monitoring-in-camunda) from the session - Learn more about [Camunda's Developer Community](https://camunda.com/developers/) - Subscribe to our monthly [Developer Community Newsletter](https://camunda.com/developers/developer-community-updates/) to receive great technical content as well as information about upcoming events and more. |
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**Speaker**

![StefanHill](https://page.camunda.com/hubfs/StefanHill.jpg)

**Stefan Hill, University of Koblenz-Landau**  
Stefan studies MSc. Computer Science at University of Koblenz-Landau. While having a background in web development, his current interests include machine learning, interdisciplinary research and data science. At present, he conducts an internship at the European Space Agency doing multispectral image processing. When he does not code, he either grows his Urban Jungle or refines his scrambling egg cooking skills.

![NicoBartmann](https://page.camunda.com/hubfs/NicoBartmann.jpeg)

**Nico Bartmann, University of Koblenz-Landau**  
Nico studies MSc. Computer Science at University of Koblenz-Landau. His goal is to use artificial intelligence to find innovative approaches to previously unsolvable problems and to implement them in practical applications. Currently, he is optimizing the railway wheel manufacturing processes with time series predictions. While his code is crispy crunchy his pork belly ist not yet.

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