9 Matching Annotations
  1. Mar 2022
  2. Jan 2022
  3. May 2021
    1. In short, MLflow makes it far easier to promote models to API endpoints on various cloud vendors compared to Kubeflow, which can do this but only with more development effort.

      MLflow seems to be much easier

    2. Bon Appétit?

      Quick comparison of MLflow and Kubeflow (check below the annotation)

    3. MLflow is a single python package that covers some key steps in model management. Kubeflow is a combination of open-source libraries that depends on a Kubernetes cluster to provide a computing environment for ML model development and production tools.

      Brief comparison of MLflow and Kubeflow

  4. Feb 2020