Importing models into Watson Machine Learning

If you have a machine learning model or neural network that was trained outside of IBM Watson Machine Learning, you can import that model into your Watson Machine Learning service.

Here, to import a trained model means:

  1. Store the trained model in your Watson Machine Learning repository
  2. [Optional] Deploy the stored model in your Watson Machine Learning service

 

Supported import formats

Table 1. Quick links: Choices for importing models
Format to import Interface options Link to details
Predictive Model Markup Language (PMML)
(.xml) file
  • Watson Studio model builder
  • Python client
  • CLI
Importing a model saved in PMML format
Spark MLlib model
(saved using the save method of the model object)
Python client Importing a saved Spark MLlib model
scikit-learn model
(saved in a pickle file)
  • Python client
  • CLI
Importing a saved scikit-learn model
TensorFlow model
(saved in a .pb file)
  • Python client
  • CLI
Importing a saved TensorFlow model
Keras model
(saved in a .h5 file)
  • Python client
  • CLI
Importing a saved Keras model