Python client example

Describes how to deploy a Decision Optimization model, create and monitor jobs, and get solutions using the Watson Machine Learning Python Client. For more information about deployment using the Watson Machine Learning Python Client, see Watson Machine Learning Client documentation.

The Python notebook Deploying a Decision Optimization model in Watson Machine Learning, available from the Community page of IBM Watson Studio, illustrates how to:
  • install the Watson Machine Learning client API
  • create a client instance
  • prepare your model archive
  • upload your model on Watson Machine Learning
  • create a deployment
  • create and monitor a job with inline data for your deployed model
  • display the solution