Advantages of Deploying Machine Learning models with Kubernetes

A Machine Learning Data scientist works hard to build a model. The model helps to solve a business problem. However, when it comes to deploying the model, there are challenges like how to scale the model, how the model can interact with different services within or outside the application, how to achieve repetitive operations, etc. To overcome this problem, Kubernetes is the best fit. In this blog, I will help you understand the basics of Kubernetes, its benefits for the deployment of Machine Learning (ML) models, and how to actually do the deployment using the Azure Kubernetes service.