MLflow is an open source technology designed to manage the lifecycle of machine learning projects. It facilitates the management, tracking and replication of machine learning experiments, offering features for metrics tracking, model management, version tracking and model deployment.
Category
Applications
Contexts
1.2.0
STABLE
2.0
STABLE
The integration of MLflow within Saagie’s DataOps platform offers substantial benefits. Firstly, it provides Data Scientists with seamless access to the MLflow ecosystem, where they can track, manage and deploy their machine learning models.
Thanks to this integration, model lifecycle management is simplified, guaranteeing model quality and traceability throughout the process.
Using MLflow with Saagie enables teams to shorten the development cycle of machine learning projects, improve collaboration between data and development teams, and ensure more efficient, iterative model maintenance.
