Setup options for Watson OpenScale
Choose a path for configuring Watson OpenScale according to your preference and level of expertise.
The Auto setup option is a guided, no-code experience that sets up and configures a machine learning environment, a database, and a sample model for you. Follow the steps in the tour to learn how to evaluate the sample model in Watson OpenScale. After the setup is complete, you can configure the service with your own database and add your own models to the dashboard.
Prepare Watson OpenScale for use by connecting to a database, setting up machine learning providers, specifying the environment type (pre-production or production), and optionally adding integrated services.
For data scientists who prefer working in notebooks, learn how to use the OpenScale REST APIs or Python SDK to provision and configure the Watson OpenScale service.
Note: This module requires that Python 3 is installed, which includes the pip package management system. For instructions, see Installing a Python module to set up model evaluation.
For more information, see APIs, SDKs, and tutorials.
Parent topic: Provisioning and launching Watson OpenScale