Location in Betahaus: floor 1 Innospace
Talk 1: Semantic Data and ML DevOps : An Industrial IoT case study
Speaker: Semih Korkmaz (Datagraph)
Abstract: ML model development and application faces challenges addressing understandability, debugging, configuration management, and operational support. This talk explores the data strategies that incorporate semantic data, data provenance, schema mutability and the relationship to effective ML development, deployment and operational practices by providing a reference implementation in an industrial IoT application.
Bio: Semih has almost a decade of experience designing and developing machine learning solutions including recommendation engines for Vodafone Mobile TV systems and Industry 4.0 applications such as reinforcement learning models for assembly tasks at Arcelik/Beko. His edge analytics projects on Siemens Systems have become accepted as a ML model deployment strategy at several manufacturing locations. Formerly, Semih was a lecturer at German Research Center for Artificial Intelligence, and a researcher Max Planck Institute.
