Federated machine learning promises to overcome emerging privacy challenges. Hence, algorithmic aspects of the topic have gained popularity in the scientific literature. However, fundamental aspects such as scalability, robustness, security, and performance in a geographically-distributed setting remain relatively unexplored. At Scaleout Systems, they are developing an open-core platform for federated machine learning operations that aims at bridging the gap between the scientific literature and real-world deployments. The aim of this talk is to share challenges and experiences in their development journey.
In this episode
Lead Machine Learning Engineer, Scaleout Systems
Marco's areas of expertise are Machine Learning, Cloud Computing, and Data Engineering. He has a master's in Bioinformatics and a Ph.D. in Scientific Computing with a focus on Large-Scale Machine Learning and Cloud. Marco enjoys following the whole life cycle of a machine learning project from exploration and modeling to operations and large-scale deployments. In his free time, Marco enjoys listening to music and playing guitar.
Demetrios is one of the main organizers of the MLOps community and currently resides in a small town outside Frankfurt, Germany. He is an avid traveller who taught English as a second language to see the world and learn about new cultures. Demetrios fell into the Machine Learning Operations world, and since, has interviewed the leading names around MLOps, Data Science, and ML. Since diving into the nitty-gritty of Machine Learning Operations he felt a strong calling to explore the ethical issues surrounding ML. When he is not conducting interviews you can find him making stone stacking with his daughter in the woods or playing the ukulele by the campfire.
Ben was the machine learning lead for Splice Machine, leading the development of their MLOps platform and Feature Store. He is now a founding software engineer at Galileo (rungalileo.io) focused on building data discovery and data quality tooling for machine learning teams. Ben also works as an adjunct professor at Washington University in St. Louis teaching concepts in cloud computing and big data analytics.