Snowpark ML release notes

This article contains the release notes for the Snowpark ML, including the following when applicable:

  • Behavior changes

  • New features

  • Customer-facing bug fixes

Version 1.0.6 (2023-09-01)

New features and updates

  • Model Development: Size of metrics result can exceed previous 8MB limit.

Bug fixes

  • Model Development fixes:

    • Fixed a bug when using simple imputer with NumPy >= 1.25.

    • Fixed a bug when inferring the type of label columns.

Version 1.0.5 (2023-08-17)

This release contains internal changes only.

Version 1.0.4 (2023-07-28)

New features and updates

  • Model Development: Input dataframes can now be joined against data loaded from staged files.

  • Model Development: Added support for non-English languages.

Version 1.0.3 (2023-07-14)

This release contains internal changes only.

Version 1.0.2 (2023-06-22)

New features and updates

  • Model Development: Added metrics:

    • d2_absolute_error_score

    • d2_pinball_score

    • explained_variance_score

    • mean_absolute_error

    • mean_absolute_percentage_error

    • mean_squared_error

Bug fixes

Model Development: accuracy_score now works when given label column names that are lists of single values.

Version 1.0.1 (2023-06-16)

Behavior changes

  • Model Development: Changed Metrics APIs to follow scikit-learn metrics modules:

    • accuracy_score, confusion_matrix, precision_recall_fscore_support, and precision_score methods move to metrics.classification.

New features and updates

  • Model Development: Added metrics:

    • f1_score

    • fbeta_score

    • recall_score

    • roc_auc_score

    • roc_curve

    • log_loss

    • precision_recall_curve

Version 1.0.0 (2023-06-09)

Initial public preview release.