Python client examples
You can deploy a Decision Optimization model, create and monitor jobs, and get solutions using the Watson Machine Learning Python Client. For more information, see Watson Machine Learning Python client documentation.
- 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
The ExtendWMLSoftwareSpec notebook in the DO-samples on the Decision Optimization GitHub shows you how to extend the Decision Optimization software specification within Watson Machine Learning to enable you to use your own pip package to add custom code and deploy it in your model and send jobs to it.