One key benefit of MLOps is the ability to automate production deployment for ML models.
MLOps, or Machine Learning Operations, is the practice of integrating machine learning models into a company's software development and infrastructure processes. It involves the collaboration of data scientists, IT professionals, and other stakeholders in the development and deployment of machine learning models.
One key benefit of MLOps is the ability to automate the deployment of machine learning models. This can be done by leveraging Modzy's pre-built integrations for popular model training tools like like Amazon SageMaker and MLFlow.
Automating the deployment of machine learning models has several advantages:
In summary, automating the deployment of machine learning models developed with popular tools like Amazon SageMaker and MLFlow via Modzy can improve efficiency, enhance reproducibility, reduce the risk of errors, and improve collaboration. These benefits make MLOps an essential practice for companies that want to make the most of their machine learning investments.
Watch this video for an overview and demo of the benefits of an automated model deployment pipeline that leverages Modzy integrations for pMLFlow and AWS SageMaker.