Tag: MLflow

  • From Spark model to production: persistence, MLflow tracking, and batch scoring

    A trained Spark ML model is only the beginning of a machine learning lifecycle. In production, the hard problems appear after training:

  • Tools: Kubeflow, Vertex AI, MLflow Projects

    Kubeflow, Vertex AI, and MLflow Projects have become essential in modern MLOps pipelines. This post compares their architectures, orchestration models, and trade-offs to help engineers choose the right tool for scalable machine learning workflows.