APIs, SDKs, and tutorials for Watson OpenScale

Although the following resources require access to the world wide web, you may find them useful in working with Watson OpenScale. In particular, the Python SDK is necessary for understanding how to work with notebooks.

Watson OpenScale API

Watson OpenScale is an enterprise-grade environment for AI applications that provides enterprises with visibility into how AI is being built, used, and delivering ROI – at the scale of their business. Use the API to help in your development work. For more information, see IBM Cloud API Docs / Watson OpenScale.

Watson OpenScale Python SDK

The Watson OpenScale Python Client is a Python library that works directly with the Watson OpenScale service. For development and automation purposes, you can use the Python client to directly configure the data mart database, add your machine learning engine, and select and monitor deployments.

Use the ibm_watson_openscale Python library to work with Watson OpenScale service. Test and deploy your models as APIs for application development, share with colleagues using this python library. For more information, see Welcome to IBM Watson OpenScale Python SDK’s documentation!.

Tutorials

The Python SDK tutorial, which provides a Jupyter Notebook to walk you through the process of creating, deploying, and viewing results of a detailed credit risk model scenario in Watson OpenScale, is also available as a tutorial for other machine learning service instances. For more information, see the Watson OpenScale sample notebook repository.

Developer internet resources

The following internet resources are designed to help you with questions or issues that you might have with Watson OpenScale:

• StackOverflow
• Create a support case

Questions and answers about resources

What internet browser does Watson OpenScale support?

The Watson OpenScale service requires the same level of browser software as is required by IBM Cloud. See the IBM Cloud Prerequisites topic for details.

Is there a command-line tool to use?

Yes! There is a ModelOps CLI tool, whose official name is the Watson OpenScale CLI model operations tool. Use it to run tasks related to the lifecycle management of machine learning models. This tool is complementary to the IBM Cloud CLI tool, augmented with the machine learning plug-in.

What version of Python can I use with Watson OpenScale?

Because Watson OpenScale is independent of your model-creation process, it supports whatever Python versions your machine learning provider supports. The Watson OpenScale Python client is a Python library that works directly with the Watson OpenScale service on IBM Cloud. For the most up-to-date version information, see the Requirements section. You can use the Python client, instead of the Watson OpenScale client UI, to directly configure a logging database, bind your machine learning engine, and select and monitor deployments. For examples of using the Python client in this way, see the Watson OpenScale sample Notebooks.