The ML in Production chapter focuses on how to deploy machine learning models into a production environment. This includes technical areas such as model serving and automation, but also focuses heavily on best practices for ML development such as MLOps.
Every day new approaches and new tools are released regarding ML in production. We do constant research on these and keep our way of working up to date with the best tooling on the market.
We build ML powered applications. Our chapter consists of multidisciplinary people to cover all phases of an ML project.
We share knowledge with the rest of the delivery organization to make sure our implementation projects are according to best practices for putting ML in production.