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sientia-dataops-model-manager
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85a8ba1e68c5edd88be81d4f1440edda1886456d
sientia-dataops-model-manager
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tests
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activities
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Bruno Domingues
85a8ba1e68
SIENTIAPDE-1255: Refactor data quality gates to training focused metrics and repositories. This commit removes the data quality gates and filters, focusing on training-specific metrics and data repositories. It also updates the README to reflect these changes, including new training metrics and a streamlined data services section.
2025-10-17 00:39:06 -03:00
..
__init__.py
SIENTIAPDE-1250: Refactor: Remove 'laborious' directory from test structure and update README.md accordingly.
2025-10-07 10:02:38 -03:00
test_activities.py
SIENTIAPDE-1255: Refactor data quality gates to training focused metrics and repositories. This commit removes the data quality gates and filters, focusing on training-specific metrics and data repositories. It also updates the README to reflect these changes, including new training metrics and a streamlined data services section.
2025-10-17 00:39:06 -03:00
test_experiment_tracking.py
SIENTIAPDE-1250: Implement experiment tracking activity with status updates, error handling, and model registration. This includes a unified update method, error message truncation, and integration into the main activities orchestrator. (236+, 2-)
2025-10-07 11:27:23 -03:00
test_minio.py
SIENTIAPDE-1250: Refactor: Remove 'laborious' directory from test structure and update README.md accordingly.
2025-10-07 10:02:38 -03:00
test_mlflow.py
SIENTIAPDE-1253: Implement activity for cleaning up temporary run directory and integrate into train model workflow. This change introduces a new activity for idempotent cleanup of the run directory after model training, replacing the direct directory removal in the workflow. This improves determinism and error handling. Also includes unit tests for the new activity.
2025-10-15 15:49:05 -03:00
test_training.py
SIENTIAPDE-1253: Implement business rule validation for training parameters. Adds a validate_business_rules method to the TrainModelParams class to enforce constraints on training parameters, improving data integrity and preventing errors. Also updates tests to include target variable in variable columns and adds tests for business rule validations.
2025-10-15 16:16:09 -03:00