Accelerated Data Science 2.8.6 is released

The following changes were made in ADS 2.8.6:

  • Resolved an issue in ads opctl build-image job-local when the build of job-local would get stuck. Updated the Python version to 3.8 in the base environment of the job-local image.
  • Fixed a bug that prevented the support of defined tags for Data Science job runs.
  • Fixed a bug in the of ads opctl that attempted to create a temporary folder in the /var/folders directory.
  • Added support for defined tags in the Data Flow application and application run.
  • Deprecated the old :py:class:`~ads.model.ModelDeploymentProperties and :py:class:`~ads.model.ModelDeployer classes, and their corresponding APIs.
  • Enabled the uploading of large size model artifacts for the :py:class:`~ads.model.ModelDeployment class.
  • Implemented validation for shape name and shape configuration details in Data Science jobs and Data Flow applications.
  • Added the capability to create ADSDataset using the Pandas accessor.
  • Made Docker dependency optional for ads opctl run.
  • Provided a prebuilt watch command for monitoring Data Science jobs with ads opctl.
  • Eliminated the legacy ads.dataflow package from ADS.

For more information, see Data Science and take a look at our Data Science blog.