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MLOps Stack
The MLOps Stack provides a comprehensive framework of tools and practices that streamline the machine learning lifecycle from data preparation and model building to deployment and monitoring, ensuring seamless integration and operational efficiency.
MLOps outcomes
- Faster and easier model deployment (including Deployment of systems of models).
- Constant model monitoring and retraining to maintain accuracy.
- Governance of the model compliance.
- Standardization of the model structure from project to project.
- Transparent tracking of models experiments.
- Efficient management of the code and dependencies.
- Model security.
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