Deploying ML Models Using Kubernetes - Analytics Vidhya

This article was published as a part of the Data Science Blogathon. A Machine Learning solution to an unambiguously defined business problem is developed by a Data Scientist ot ML Engineer. The Model development process undergoes multiple iterations and finally, a model which has acceptable performance metrics on test data is taken to the production environment. Taking the final chosen model reaching it out to the users is called deployment and there are a few options available to deploy a model. Kubernetes(also called k8s) is one of the open-source tools used for deploying our applications.