What Does it Mean to Deploy a Machine Learning Model?

Data Science, a promising field that continues to attract more and more companies, is struggling to be integrated into industrialization processes. In most cases, machine learning (ML) models are implemented offline in a scientific research context. Almost 90% of the models created are never deployed in production conditions. Deployment can be defined as a process by which an ML model is integrated into an existing production environment to achieve effective data-driven business decisions. It is one of the last stages of the machine learning life cycle.