New AutoAI capabilities generally available for Watson Studio and Watson Machine Learning and phase-out of Model Builder.
We are delighted to announce the general availability of AutoAI in Watson Studio as of May 31, 2019. With this release, we extend the portfolio of best-in-class data science and machine learning tools available in Watson Studio, the premier enterprise data science platform. This release focuses on the automation of the end-to-end model building lifecycle, from data ingestion to model deployment. By automating tasks that typically take data scientists days or weeks, Watson Studio continues its mission of boosting the productivity of data science teams large and small.
Getting started with AutoAI
To get started, any Watson Studio user can now add an AutoAI Experiment asset to their new or existing projects. Once added, simply select a data set and a field to predict or classify and the automation handles the rest.
Once the AutoAI training job completes, you can easily compare the machine learning pipelines to evaluate performance and gain intuition about the feature importance of fields used for the model from the raw data. After evaluating, any of the pipelines can easily be saved to your Watson Machine Learning repository and deployed as a web service deployment with a couple clicks.
Phasing out Watson Machine Learning Model Builder
Related to this announcement, we will also be phasing out the Watson Machine Learning Model Builder tool on July 31, 2019. Models trained with Model Builder and deployed to Watson Machine Learning will continue to be supported, but following this date, no new models can be trained using Model Builder.