What is ML-Ops? Why is it important? (MLOps-1)
Businesses around the globe use machine learning to predict their sales, profits, costs, performance, and use these predictions to build actionable insights. These insights help decision-makers to take the right decision according to the current situation after learning from historical experiences.
While ML-teams focus on modelling and SW teams focus on development, I could rarely find a team focusing on ML operations or MLOps for short. in this article, we will explain what is MLOps and why it is important.
What is MLOps?
MLOps has two interpretations, ML-Development Operations and ML-Runtime Operations. ML-DevOps focuses on taking the model from coding to production enabling the CI/CD feature (Continuous Integration/Continuous Deployment). This feature will take the code through all the stages of source control, virtualization, building, deployment, hosting and scaling.
