ROBUST MLOPS FRAMEWORKS FOR AUTOMATING THE AI/ML LIFECYCLE IN CLOUD ENVIRONMENTS

Abstract

It has become clear that MLOps is an important way to manage the whole lifecycle of AI/ML models, from creation to deployment. This article talks about an all-inclusive MLOps system made to make training, validating, deploying, and monitoring models in the cloud automatic. To make the AI/ML process easier, the framework has scalable cloud-native tools, continuous integration/continuous deployment (CI/CD) pipelines, and automated hyperparameter optimization. Case studies show that models are more reliable, they can be deployed faster, and they have less operating overhead. The importance of these developments for the widespread use of AI in businesses cannot be overstated.