Evaluating AI models with Watson OpenScale

IBM Watson OpenScale tracks and measures outcomes from your AI models, and helps ensure that they remain fair, explainable, and compliant no matter where your models were built or are running. Watson OpenScale also detects and helps correct the drift in accuracy when an AI model is in production.

Required service
Watson Machine Learning
Training data format
Relational: Tables in relational data sources
Tabular: Excel files (.xls or .xlsx), CSV files
Textual: In the supported relational tables or files
Connected data
Cloud Object Storage (infrastructure)
Db2
Data size
Any

Service This service is not available by default. An administrator must install this service on the IBM Cloud Pak for Data platform, and you must be given access to the service. To determine whether the service is installed, open the Services catalog and check whether the service is enabled.

Enterprises use model evaluation as part of an AI governance strategy to make sure that models in development and production meet established compliance standards. This approach ensures that AI models are free from bias, can be easily explained and understood by business users, and are auditable in business transactions. You can evaluate models regardless of the tools and frameworks that you use to build and run models.

Watch this short video to learn more about Watson OpenScale:

This video provides a visual method to learn the concepts and tasks in this documentation.