Paul Rupprecht leading Machine Learning Projects & MLOps at Merantix Momentum (S5/15)

Streamlining Machine Learning Bestrebungen | Interview with Paul Rupprecht | Erium Podcast


In this episode of The Erium Podcast, we dive into the world of machine learning and data science with Paul Rupprecht, the Senior Project Manager at Merantix Momentum. Join us as we discuss Paul’s role in bridging the gap between technology and business, the importance of MLOps, and how companies can streamline their machine learning efforts.

Paul Rupprecht is an experienced professional in building data science pipelines and implementing projects in predictive maintenance, predictive quality, and computer vision. With his expertise as the Senior Project Manager at Merantix Momentum, a leading machine learning service provider based in Berlin, Paul brings a wealth of knowledge to the table.

At Merantix Momentum, Paul and his team work on a wide range of projects across various industries, including manufacturing, insurance, and more. With a focus on KI Podcast, Data Science, and Machine Learning, this interview offers valuable insights into the world of machine learning and its impact on businesses.

To learn more about Paul Rupprecht and his role at Merantix Momentum, check out [Merantix Momentum]( and [AI Campus](

[Tune in to the full episode]( to gain valuable insights from Paul Rupprecht’s expertise in MLOps and machine learning projects. Don’t miss out on this informative conversation!

Keywords/Tags: KI Podcast, Data Science, Machine Learning, Interview, Paul Rupprecht, Merantix Momentum, MLOps

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Paul Pupprecht leitet als Senior Projektmanager das Team Machine Learning Projects & MLOps bei Merantix Momentum, einem Machine Learning Service Provider mit Sitz am AI Campus in Berlin. Dabei nutzt er seine Erfahrung im Bau von Data Science Pipelines und der Umsetzung von Projekten in den Bereichen Predictive Maintenance, Predictive Quality und Computer Vision. In dieser Folge von The Erium Podcast sprechen wir mit Paul über seine Schnittstellenfunktion zwischen Technologie & Business, MLOps und wie Konzerne ihre Machine Learning Bestrebungen streamlinen.

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