Operationalization is the process of publishing models and code as web services and the consumption of these services to produce business results.

Azure Machine Learning Operationalization is a component of the Azure CLI that enables operationalization of models that you create through Vienna that use the CNTK, SPARK, and Python machine learning platforms.

Documentation

• Operationalization Overview

• Installation guides

  • Getting started
  • Installing the machine learning operationalization stack on Ubuntu Linux
  • Installing the operationalization stack on Windows 10 or Windows Server
  • Installing the machine learning operationalization stack on the head node of an HDInsight cluster

• Tutorials and samples:

  • Spark
    • Realtime web service tutorial
  • Python
    • Realtime web service tutorial
    • Code Sample
  • CNTK
    • Realtime web service tutorial
    • Code Sample

• How to

  • How to enable logging
  • How to operationalize a remotely stored model
  • How to use remotely stored data in a batch service call
  • Operationalizing Batch Processing of Machine Learning Models on Azure (Preview)
  • How to scale operationalization on your ACS cluster
  • Consuming the web service
  • Troubleshooting the web service
  • Creating score.py file

• Technical Articles:

  • Command-Line Interface Reference
  • Model Management Service Overview
  • Model Management API Reference

• FAQ