Mátyás studied computer science and applied economics in Budapest, then completed an international master about data science and innovation/entrepreneurship. During these years he worked with research institutes, international enterprises and small startups alike. Currently, he is working as a solution engineer at Avalon by Devoteam, mostly using technologies such as GCP, kubernetes and kubeflow.

Abstract talk
Kubeflow is a relatively new open source framework released by Google. It provides the ability to build reproducible Machine Learning pipelines with validation and A/B testing. We will show how to best organize your data engineering processes, teams around Kubeflow to maximize your use of data.