MLflow is a highly available platform for managing a lifecycle of machine learning experiments. You can track them, organize models into detailed versions, compare metrics and deploy customized models. Managed MLflow in Nebius AI Cloud enables you to access model artifacts, training results and tuned hyperparameters in a single interface. As a result, you can reproduce ML experiments and deploy the best performing models. The service is available in all Nebius AI Cloud regions exceptDocumentation Index
Fetch the complete documentation index at: https://docs.nebius.com/llms.txt
Use this file to discover all available pages before exploring further.
eu-north2 and eu-west1.
Getting started
Create your first cluster and run an experiment in it
Creating and modifying clusters
Create Managed MLflow clusters via Nebius AI Cloud interfaces
Monitoring a Managed MLflow cluster state
Control resource usage and monitor your cluster health