MLOps is a set of
practices
used to maintain, deploy and manage machine learning models in production.
In a nutshell, MLOps engineer
work
started once the build and tested.
The MLOps engineer role is relatively
new
and its demand is growing day by day.
MLOps engineer evaluates the model performance once the machine learning model is deployed in
production
.
MLOps engineers should be
aware
of DevOps, machine learning, and data engineering technologies.
MLOps engineers also need to
perform
model governance, model Monitoring, and model versioning.
MLOps engineers should be aware of tools like
MLFlow and kubeflow
which are used to manage the life cycle of machine learning models.
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