AutoAI experiment and pipeline refinery with WML-Client
Watson Machine Learning (Deprecated)
Sep 11, 2020

Attention: This sample is deprecated and is associated with a legacy, v1 Watson Machine Learning service instance. v2 service instances were rolled out on September 1, 2020. For details, see What's New. During the migration period, you can still run samples and examples associated with a legacy service instance. However, note the following requirements and restrictions to do so:

  • You must use a v1 service instance and associated credentials to run a v1 sample or example. Follow the authentication steps to authenticate with deprecated samples.
  • Lite users can use existing v1 service credentials, but cannot create new credentials.
  • Standard and Professional users can use existing v1 service credentials and can also create new v1 service credentials. The Credentials page was removed from the IBM Cloud Services catalog, so follow the steps in Generating legacy Watson Machine Learning credentials to create new credentials using the IBM Cloud CLI.

Learn how to use AutoAI experiments in this notebook by getting a German credit data set and train the model to predict banking credit. Then, compare several trained models for quality and select best one for further refinement, refine it and deploy it online and score the model. This notebook runs in a Python 3 environment.

Drag and drop files to add data source.