Machine learning models are powering the finance, retail, energy, and healthcare sectors. The growth in popularity of AI comes with some new challenges; models cannot live on their own and have to be incorporated into production environment. To that extent programming frameworks, tools and infrastructure are evolving at an enormous pace. New architectures and design patterns have arrived to work with these new technologies. One important field of research is MLOps, which has evolved into a way of working and set of best practices to deploy, test, manage, and monitor machine learning models in production. In this session, we’ll explore this relatively new subject. Bas will explain the need for MLOps, dive into the tools and techniques, and give some examples of real-world solutions.