Nobody likes throwing good food away, while everybody likes to get a fresh meal on a long-distance flight. In to order take just the right amount of meals on board, KLM Royal Dutch Airlines successfully executed a project to improve their forecast of the number of passengers on-board every flight. In this talk, we walk you through the full-cycle process of designing, developing and industrializing a machine-learning model for this supply chain management use case. We discuss the requirements, data sources, evaluation metrics, gradient boosting decision trees algorithm and microservice architecture. Throughout the talk we highlight challenges, solutions and learnings.
Bio Daan
Daan Debie is Director Engineering & Architecture at KLM Operations Decision Support. After working for years as a software engineer and data engineer at various companies, he now leads a team that builds decision support tools for KLM.
Bio Alexander
Alexander Backus is a lead data scientist and big data consultant at BigData Republic, with experience in various sectors, including energy, finance, airline and retail. After obtaining a PhD in cognitive neuroscience, he now provides machine learning and big data expertise to organizations such as KLM Royal Dutch Airlines.
