• MLFlow 0.9.0
MLflow
  • Quickstart
  • Tutorial
  • Concepts
  • MLflow Tracking
  • MLflow Projects
  • MLflow Models
  • Command-Line Interface
  • Python API
    • mlflow
    • mlflow.azureml
    • mlflow.entities
    • mlflow.h2o
    • mlflow.keras
    • mlflow.mleap
    • mlflow.models
    • mlflow.projects
    • mlflow.pyfunc
    • mlflow.pytorch
    • mlflow.sagemaker
    • mlflow.sklearn
    • mlflow.spark
    • mlflow.tensorflow
    • mlflow.tracking
  • R API
  • Java API
  • REST API

Contribute

  • Documentation
  • Python API
  • Edit on GitHub

Python API

The MLflow Python API is organized into the following modules. The most common functions are also exposed in the mlflow module, so we recommend starting there.

  • mlflow
  • mlflow.azureml
  • mlflow.entities
  • mlflow.h2o
  • mlflow.keras
  • mlflow.mleap
  • mlflow.models
  • mlflow.projects
  • mlflow.pyfunc
    • Filesystem format
      • MLModel configuration
    • Inference API
    • Creating custom Pyfunc models
      • Workflows
      • Which workflow is right for my use case?
  • mlflow.pytorch
  • mlflow.sagemaker
  • mlflow.sklearn
  • mlflow.spark
  • mlflow.tensorflow
  • mlflow.tracking

See also an index of all functions and classes.

Previous Next

© Databricks 2019. All rights reserved.