- Big Model Registry Refresh - Fixed API discrepancies between register_model & log_model. - Model can be referred by Name + Version (no opaque internal id is required)
New Features
- Model Registry: Added support save/load/deploy SKL & XGB Models
0.2.3
Bug Fixes
- Allow using OneHotEncoder along with sklearn style estimators in a pipeline.
New Features
- Model Registry: Added support for delete_model. Use delete_artifact = False to not delete the underlying model data but just unregister.
0.2.2
New Features
- Initial version of snowflake-ml modeling package. - Provide support for training most of scikit-learn and xgboost estimators and transformers.
Bug Fixes
- Minor fixes in preprocessing package.
0.2.1
New Features
- New in Preprocessing: - SimpleImputer - Covariance Matrix - Optimization of Ordinal Encoder client computations.
Bug Fixes
- Minor fixes in OneHotEncoder.
0.2.0
New Features
- Model Registry - PyTorch & Tensorflow connector file generic FileSet API - New to Preprocessing: - Binarizer - Normalizer - Pearson correlation Matrix - Optimization in Ordinal Encoder to cache vocabulary in temp tables.
0.1.3
New Features
- Initial version of transformers including: - Label Encoder - Max Abs Scaler - Min Max Scaler - One Hot Encoder - Ordinal Encoder - Robust Scaler - Standard Scaler